Overview

Dataset statistics

Number of variables59
Number of observations109
Missing cells2330
Missing cells (%)36.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.4 KiB
Average record size in memory473.2 B

Variable types

Numeric12
Categorical38
Unsupported9

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-14" Constant
url has a high cardinality: 109 distinct values High cardinality
name has a high cardinality: 95 distinct values High cardinality
_links.self.href has a high cardinality: 109 distinct values High cardinality
_embedded.show.url has a high cardinality: 61 distinct values High cardinality
_embedded.show.name has a high cardinality: 61 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 56 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 54 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 54 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 61 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 61 distinct values High cardinality
id is highly correlated with rating.average and 3 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 5 other fieldsHigh correlation
number is highly correlated with rating.average and 2 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 8 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 4 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 9 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 11 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.updated is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 6 other fieldsHigh correlation
id is highly correlated with rating.average and 1 other fieldsHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with season and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 6 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 5 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with season and 9 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 6 other fieldsHigh correlation
id is highly correlated with rating.averageHigh correlation
season is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 3 other fieldsHigh correlation
rating.average is highly correlated with idHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with runtime and 6 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with season and 5 other fieldsHigh correlation
id is highly correlated with airstamp and 30 other fieldsHigh correlation
name is highly correlated with season and 39 other fieldsHigh correlation
season is highly correlated with name and 23 other fieldsHigh correlation
number is highly correlated with name and 34 other fieldsHigh correlation
airtime is highly correlated with name and 35 other fieldsHigh correlation
airstamp is highly correlated with id and 41 other fieldsHigh correlation
runtime is highly correlated with name and 40 other fieldsHigh correlation
summary is highly correlated with id and 32 other fieldsHigh correlation
rating.average is highly correlated with name and 20 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.type is highly correlated with name and 40 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.status is highly correlated with airstamp and 33 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with name and 41 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with name and 41 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with name and 34 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with name and 32 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with name and 20 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with name and 38 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
image.medium is highly correlated with id and 37 other fieldsHigh correlation
image.original is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 34 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 34 other fieldsHigh correlation
runtime has 5 (4.6%) missing values Missing
image has 109 (100.0%) missing values Missing
summary has 79 (72.5%) missing values Missing
rating.average has 98 (89.9%) missing values Missing
_embedded.show.runtime has 22 (20.2%) missing values Missing
_embedded.show.ended has 53 (48.6%) missing values Missing
_embedded.show.officialSite has 13 (11.9%) missing values Missing
_embedded.show.rating.average has 83 (76.1%) missing values Missing
_embedded.show.network has 109 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 59 (54.1%) missing values Missing
_embedded.show.webChannel.country.code has 59 (54.1%) missing values Missing
_embedded.show.webChannel.country.timezone has 59 (54.1%) missing values Missing
_embedded.show.webChannel.officialSite has 46 (42.2%) missing values Missing
_embedded.show.dvdCountry has 109 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 106 (97.2%) missing values Missing
_embedded.show.externals.thetvdb has 15 (13.8%) missing values Missing
_embedded.show.externals.imdb has 51 (46.8%) missing values Missing
_embedded.show.image.medium has 13 (11.9%) missing values Missing
_embedded.show.image.original has 13 (11.9%) missing values Missing
_embedded.show.summary has 22 (20.2%) missing values Missing
_embedded.show._links.nextepisode.href has 102 (93.6%) missing values Missing
image.medium has 75 (68.8%) missing values Missing
image.original has 75 (68.8%) missing values Missing
_embedded.show.network.id has 103 (94.5%) missing values Missing
_embedded.show.network.name has 103 (94.5%) missing values Missing
_embedded.show.network.country.name has 103 (94.5%) missing values Missing
_embedded.show.network.country.code has 103 (94.5%) missing values Missing
_embedded.show.network.country.timezone has 103 (94.5%) missing values Missing
_embedded.show.network.officialSite has 109 (100.0%) missing values Missing
_embedded.show.webChannel.country has 109 (100.0%) missing values Missing
_embedded.show.image has 109 (100.0%) missing values Missing
_embedded.show.webChannel has 109 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-05 04:39:19.999531
Analysis finished2022-09-05 04:39:36.031363
Duration16.03 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2026682.917
Minimum1945592
Maximum2368297
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:36.074364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1945592
5-th percentile1971207.4
Q11977836
median1985645
Q32005524
95-th percentile2264939.6
Maximum2368297
Range422705
Interquartile range (IQR)27688

Descriptive statistics

Standard deviation93659.99745
Coefficient of variation (CV)0.04621344397
Kurtosis3.395118793
Mean2026682.917
Median Absolute Deviation (MAD)7811
Skewness2.086646979
Sum220908438
Variance8772195122
MonotonicityNot monotonic
2022-09-04T23:39:36.160362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19824031
 
0.9%
19787801
 
0.9%
19880551
 
0.9%
19880541
 
0.9%
19880531
 
0.9%
19880521
 
0.9%
19878081
 
0.9%
19873251
 
0.9%
19873241
 
0.9%
19873231
 
0.9%
Other values (99)99
90.8%
ValueCountFrequency (%)
19455921
0.9%
19679291
0.9%
19690621
0.9%
19707671
0.9%
19710561
0.9%
19712071
0.9%
19712081
0.9%
19712091
0.9%
19712101
0.9%
19712111
0.9%
ValueCountFrequency (%)
23682971
0.9%
23369091
0.9%
23181041
0.9%
22649421
0.9%
22649411
0.9%
22649401
0.9%
22649391
0.9%
22649381
0.9%
22111361
0.9%
21975951
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-05
 
1
https://www.tvmaze.com/episodes/1978780/kuad-wicha-by-brands-summer-camp-1x06-episode-6
 
1
https://www.tvmaze.com/episodes/1988055/forever-love-1x04-episode-4
 
1
https://www.tvmaze.com/episodes/1988054/forever-love-1x03-episode-3
 
1
https://www.tvmaze.com/episodes/1988053/forever-love-1x02-episode-2
 
1
Other values (104)
104 

Length

Max length155
Median length91
Mean length76.90825688
Min length58

Characters and Unicode

Total characters8383
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1982403/volk-1x05-seria-05
2nd rowhttps://www.tvmaze.com/episodes/1982404/volk-1x06-seria-06
3rd rowhttps://www.tvmaze.com/episodes/2140387/going-seventeen-2020-12-14-going-vs-seventeen-1
4th rowhttps://www.tvmaze.com/episodes/1945592/my-little-invisible-being-1x12-episode-12
5th rowhttps://www.tvmaze.com/episodes/2065442/the-wonderland-of-ten-thousands-4x29-episode-29-157

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-051
 
0.9%
https://www.tvmaze.com/episodes/1978780/kuad-wicha-by-brands-summer-camp-1x06-episode-61
 
0.9%
https://www.tvmaze.com/episodes/1988055/forever-love-1x04-episode-41
 
0.9%
https://www.tvmaze.com/episodes/1988054/forever-love-1x03-episode-31
 
0.9%
https://www.tvmaze.com/episodes/1988053/forever-love-1x02-episode-21
 
0.9%
https://www.tvmaze.com/episodes/1988052/forever-love-1x01-episode-11
 
0.9%
https://www.tvmaze.com/episodes/1987808/v-ritme-kolbasy-1x04-gibel-goliafa1
 
0.9%
https://www.tvmaze.com/episodes/1987325/beauty-and-the-boss-1x05-episode-51
 
0.9%
https://www.tvmaze.com/episodes/1987324/beauty-and-the-boss-1x04-episode-41
 
0.9%
https://www.tvmaze.com/episodes/1987323/beauty-and-the-boss-1x03-episode-31
 
0.9%
Other values (99)99
90.8%

Length

2022-09-04T23:39:36.251377image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-051
 
0.9%
https://www.tvmaze.com/episodes/1986023/la-vida-moderna-7x55-caca-en-la-pared1
 
0.9%
https://www.tvmaze.com/episodes/2140387/going-seventeen-2020-12-14-going-vs-seventeen-11
 
0.9%
https://www.tvmaze.com/episodes/1945592/my-little-invisible-being-1x12-episode-121
 
0.9%
https://www.tvmaze.com/episodes/2065442/the-wonderland-of-ten-thousands-4x29-episode-29-1571
 
0.9%
https://www.tvmaze.com/episodes/2071477/youths-in-the-breeze-1x07-the-boy-and-the-cat-071
 
0.9%
https://www.tvmaze.com/episodes/2071478/youths-in-the-breeze-1x08-the-boy-and-the-cat-081
 
0.9%
https://www.tvmaze.com/episodes/2080225/supreme-god-emperor-1x63-episode-631
 
0.9%
https://www.tvmaze.com/episodes/1977322/stjernestov-1x14-episode-141
 
0.9%
https://www.tvmaze.com/episodes/2003096/slepaa-10x100-cuzaa-igra1
 
0.9%
Other values (99)99
90.8%

Most occurring characters

ValueCountFrequency (%)
e732
 
8.7%
-639
 
7.6%
t567
 
6.8%
/545
 
6.5%
s511
 
6.1%
o410
 
4.9%
w353
 
4.2%
p319
 
3.8%
a309
 
3.7%
i301
 
3.6%
Other values (30)3697
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5595
66.7%
Decimal Number1277
 
15.2%
Other Punctuation872
 
10.4%
Dash Punctuation639
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e732
13.1%
t567
 
10.1%
s511
 
9.1%
o410
 
7.3%
w353
 
6.3%
p319
 
5.7%
a309
 
5.5%
i301
 
5.4%
m273
 
4.9%
h237
 
4.2%
Other values (16)1583
28.3%
Decimal Number
ValueCountFrequency (%)
1265
20.8%
2179
14.0%
0156
12.2%
9131
10.3%
7108
8.5%
8103
 
8.1%
490
 
7.0%
389
 
7.0%
579
 
6.2%
677
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/545
62.5%
.218
 
25.0%
:109
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-639
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5595
66.7%
Common2788
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e732
13.1%
t567
 
10.1%
s511
 
9.1%
o410
 
7.3%
w353
 
6.3%
p319
 
5.7%
a309
 
5.5%
i301
 
5.4%
m273
 
4.9%
h237
 
4.2%
Other values (16)1583
28.3%
Common
ValueCountFrequency (%)
-639
22.9%
/545
19.5%
1265
9.5%
.218
 
7.8%
2179
 
6.4%
0156
 
5.6%
9131
 
4.7%
:109
 
3.9%
7108
 
3.9%
8103
 
3.7%
Other values (4)335
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e732
 
8.7%
-639
 
7.6%
t567
 
6.8%
/545
 
6.5%
s511
 
6.1%
o410
 
4.9%
w353
 
4.2%
p319
 
3.8%
a309
 
3.7%
i301
 
3.6%
Other values (30)3697
44.1%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct95
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Episode 3
 
4
Episode 4
 
3
Episode 24
 
2
Episode 22
 
2
Episode 1
 
2
Other values (90)
96 

Length

Max length93
Median length62
Mean length17.56880734
Min length5

Characters and Unicode

Total characters1915
Distinct characters118
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)77.1%

Sample

1st rowСерия 05
2nd rowСерия 06
3rd rowGOING VS SEVENTEEN #1
4th rowEpisode 12
5th rowEpisode 29 (157)

Common Values

ValueCountFrequency (%)
Episode 34
 
3.7%
Episode 43
 
2.8%
Episode 242
 
1.8%
Episode 222
 
1.8%
Episode 12
 
1.8%
Episode 82
 
1.8%
Episode 62
 
1.8%
Episode 252
 
1.8%
Episode 52
 
1.8%
Episode 22
 
1.8%
Other values (85)86
78.9%

Length

2022-09-04T23:39:36.337353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode40
 
11.0%
the21
 
5.8%
chapter13
 
3.6%
9
 
2.5%
37
 
1.9%
16
 
1.6%
26
 
1.6%
bölum5
 
1.4%
45
 
1.4%
54
 
1.1%
Other values (210)249
68.2%

Most occurring characters

ValueCountFrequency (%)
256
 
13.4%
e164
 
8.6%
o100
 
5.2%
i86
 
4.5%
s85
 
4.4%
a80
 
4.2%
t69
 
3.6%
r69
 
3.6%
p64
 
3.3%
d61
 
3.2%
Other values (108)881
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1145
59.8%
Uppercase Letter306
 
16.0%
Space Separator256
 
13.4%
Decimal Number141
 
7.4%
Other Punctuation53
 
2.8%
Dash Punctuation6
 
0.3%
Close Punctuation3
 
0.2%
Open Punctuation3
 
0.2%
Math Symbol2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e164
14.3%
o100
 
8.7%
i86
 
7.5%
s85
 
7.4%
a80
 
7.0%
t69
 
6.0%
r69
 
6.0%
p64
 
5.6%
d61
 
5.3%
h46
 
4.0%
Other values (42)321
28.0%
Uppercase Letter
ValueCountFrequency (%)
E52
17.0%
T32
 
10.5%
C32
 
10.5%
S17
 
5.6%
D14
 
4.6%
B13
 
4.2%
N12
 
3.9%
A11
 
3.6%
I10
 
3.3%
F9
 
2.9%
Other values (31)104
34.0%
Decimal Number
ValueCountFrequency (%)
232
22.7%
129
20.6%
317
12.1%
014
9.9%
413
9.2%
610
 
7.1%
58
 
5.7%
77
 
5.0%
87
 
5.0%
94
 
2.8%
Other Punctuation
ValueCountFrequency (%)
:18
34.0%
,9
17.0%
.8
15.1%
'8
15.1%
#6
 
11.3%
&2
 
3.8%
?1
 
1.9%
1
 
1.9%
Close Punctuation
ValueCountFrequency (%)
)2
66.7%
]1
33.3%
Open Punctuation
ValueCountFrequency (%)
(2
66.7%
[1
33.3%
Space Separator
ValueCountFrequency (%)
256
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1326
69.2%
Common464
 
24.2%
Cyrillic125
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e164
 
12.4%
o100
 
7.5%
i86
 
6.5%
s85
 
6.4%
a80
 
6.0%
t69
 
5.2%
r69
 
5.2%
p64
 
4.8%
d61
 
4.6%
E52
 
3.9%
Other values (41)496
37.4%
Cyrillic
ValueCountFrequency (%)
и11
 
8.8%
а9
 
7.2%
е9
 
7.2%
о8
 
6.4%
р7
 
5.6%
С6
 
4.8%
м5
 
4.0%
т5
 
4.0%
ь4
 
3.2%
л4
 
3.2%
Other values (32)57
45.6%
Common
ValueCountFrequency (%)
256
55.2%
232
 
6.9%
129
 
6.2%
:18
 
3.9%
317
 
3.7%
014
 
3.0%
413
 
2.8%
610
 
2.2%
,9
 
1.9%
.8
 
1.7%
Other values (15)58
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1782
93.1%
Cyrillic125
 
6.5%
None7
 
0.4%
Punctuation1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
 
14.4%
e164
 
9.2%
o100
 
5.6%
i86
 
4.8%
s85
 
4.8%
a80
 
4.5%
t69
 
3.9%
r69
 
3.9%
p64
 
3.6%
d61
 
3.4%
Other values (62)748
42.0%
Cyrillic
ValueCountFrequency (%)
и11
 
8.8%
а9
 
7.2%
е9
 
7.2%
о8
 
6.4%
р7
 
5.6%
С6
 
4.8%
м5
 
4.0%
т5
 
4.0%
ь4
 
3.2%
л4
 
3.2%
Other values (32)57
45.6%
None
ValueCountFrequency (%)
ö5
71.4%
å1
 
14.3%
é1
 
14.3%
Punctuation
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct14
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.266055
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:36.410381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile1224.4
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation462.1150178
Coefficient of variation (CV)4.044202083
Kurtosis13.9048052
Mean114.266055
Median Absolute Deviation (MAD)0
Skewness3.955672094
Sum12455
Variance213550.2897
MonotonicityNot monotonic
2022-09-04T23:39:36.486285image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
162
56.9%
217
 
15.6%
20206
 
5.5%
46
 
5.5%
33
 
2.8%
73
 
2.8%
63
 
2.8%
182
 
1.8%
122
 
1.8%
101
 
0.9%
Other values (4)4
 
3.7%
ValueCountFrequency (%)
162
56.9%
217
 
15.6%
33
 
2.8%
46
 
5.5%
63
 
2.8%
73
 
2.8%
91
 
0.9%
101
 
0.9%
122
 
1.8%
182
 
1.8%
ValueCountFrequency (%)
20206
5.5%
311
 
0.9%
301
 
0.9%
271
 
0.9%
182
 
1.8%
122
 
1.8%
101
 
0.9%
91
 
0.9%
73
2.8%
63
2.8%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct42
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.57798165
Minimum1
Maximum341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:36.569470image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q324
95-th percentile94
Maximum341
Range340
Interquartile range (IQR)20

Descriptive statistics

Standard deviation57.75816338
Coefficient of variation (CV)2.094357887
Kurtosis17.17041489
Mean27.57798165
Median Absolute Deviation (MAD)5
Skewness4.048556314
Sum3006
Variance3336.005437
MonotonicityNot monotonic
2022-09-04T23:39:36.661696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
49
 
8.3%
38
 
7.3%
28
 
7.3%
17
 
6.4%
67
 
6.4%
56
 
5.5%
86
 
5.5%
125
 
4.6%
104
 
3.7%
74
 
3.7%
Other values (32)45
41.3%
ValueCountFrequency (%)
17
6.4%
28
7.3%
38
7.3%
49
8.3%
56
5.5%
67
6.4%
74
3.7%
86
5.5%
93
 
2.8%
104
3.7%
ValueCountFrequency (%)
3411
0.9%
3021
0.9%
3011
0.9%
2341
0.9%
1511
0.9%
1001
0.9%
851
0.9%
821
0.9%
651
0.9%
631
0.9%

type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
regular
109 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters763
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular109
100.0%

Length

2022-09-04T23:39:36.747359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:36.821211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
regular109
100.0%

Most occurring characters

ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter763
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin763
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII763
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r218
28.6%
e109
14.3%
g109
14.3%
u109
14.3%
l109
14.3%
a109
14.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2020-12-14
109 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1090
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-14
2nd row2020-12-14
3rd row2020-12-14
4th row2020-12-14
5th row2020-12-14

Common Values

ValueCountFrequency (%)
2020-12-14109
100.0%

Length

2022-09-04T23:39:36.902229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:36.979772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-14109
100.0%

Most occurring characters

ValueCountFrequency (%)
2327
30.0%
0218
20.0%
-218
20.0%
1218
20.0%
4109
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number872
80.0%
Dash Punctuation218
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2327
37.5%
0218
25.0%
1218
25.0%
4109
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1090
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2327
30.0%
0218
20.0%
-218
20.0%
1218
20.0%
4109
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2327
30.0%
0218
20.0%
-218
20.0%
1218
20.0%
4109
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1000.0 B
74 
20:00
27 
12:00
 
1
06:00
 
1
17:35
 
1
Other values (5)
 
5

Length

Max length5
Median length0
Mean length1.605504587
Min length0

Characters and Unicode

Total characters175
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.3%

Sample

1st row
2nd row
3rd row
4th row12:00
5th row

Common Values

ValueCountFrequency (%)
74
67.9%
20:0027
 
24.8%
12:001
 
0.9%
06:001
 
0.9%
17:351
 
0.9%
00:001
 
0.9%
19:001
 
0.9%
20:151
 
0.9%
17:001
 
0.9%
21:001
 
0.9%

Length

2022-09-04T23:39:37.039562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:37.126202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
20:0027
77.1%
12:001
 
2.9%
06:001
 
2.9%
17:351
 
2.9%
00:001
 
2.9%
19:001
 
2.9%
20:151
 
2.9%
17:001
 
2.9%
21:001
 
2.9%

Most occurring characters

ValueCountFrequency (%)
097
55.4%
:35
 
20.0%
230
 
17.1%
16
 
3.4%
72
 
1.1%
52
 
1.1%
61
 
0.6%
31
 
0.6%
91
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number140
80.0%
Other Punctuation35
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
097
69.3%
230
 
21.4%
16
 
4.3%
72
 
1.4%
52
 
1.4%
61
 
0.7%
31
 
0.7%
91
 
0.7%
Other Punctuation
ValueCountFrequency (%)
:35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
097
55.4%
:35
 
20.0%
230
 
17.1%
16
 
3.4%
72
 
1.1%
52
 
1.1%
61
 
0.6%
31
 
0.6%
91
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
097
55.4%
:35
 
20.0%
230
 
17.1%
16
 
3.4%
72
 
1.1%
52
 
1.1%
61
 
0.6%
31
 
0.6%
91
 
0.6%

airstamp
Categorical

HIGH CORRELATION

Distinct17
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2020-12-14T12:00:00+00:00
78 
2020-12-14T17:00:00+00:00
 
5
2020-12-14T04:00:00+00:00
 
5
2020-12-14T09:00:00+00:00
 
5
2020-12-14T00:00:00+00:00
 
2
Other values (12)
14 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2725
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)9.2%

Sample

1st row2020-12-14T00:00:00+00:00
2nd row2020-12-14T00:00:00+00:00
3rd row2020-12-14T03:00:00+00:00
4th row2020-12-14T04:00:00+00:00
5th row2020-12-14T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-14T12:00:00+00:0078
71.6%
2020-12-14T17:00:00+00:005
 
4.6%
2020-12-14T04:00:00+00:005
 
4.6%
2020-12-14T09:00:00+00:005
 
4.6%
2020-12-14T00:00:00+00:002
 
1.8%
2020-12-14T11:00:00+00:002
 
1.8%
2020-12-14T19:00:00+00:002
 
1.8%
2020-12-15T01:00:00+00:001
 
0.9%
2020-12-14T22:00:00+00:001
 
0.9%
2020-12-14T19:15:00+00:001
 
0.9%
Other values (7)7
 
6.4%

Length

2022-09-04T23:39:37.209366image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-14t12:00:00+00:0078
71.6%
2020-12-14t04:00:00+00:005
 
4.6%
2020-12-14t09:00:00+00:005
 
4.6%
2020-12-14t17:00:00+00:005
 
4.6%
2020-12-14t00:00:00+00:002
 
1.8%
2020-12-14t11:00:00+00:002
 
1.8%
2020-12-14t19:00:00+00:002
 
1.8%
2020-12-14t15:00:00+00:001
 
0.9%
2020-12-14t05:00:00+00:001
 
0.9%
2020-12-14t05:35:00+00:001
 
0.9%
Other values (7)7
 
6.4%

Most occurring characters

ValueCountFrequency (%)
01105
40.6%
2408
 
15.0%
:327
 
12.0%
1313
 
11.5%
-218
 
8.0%
4113
 
4.1%
T109
 
4.0%
+109
 
4.0%
98
 
0.3%
57
 
0.3%
Other values (3)8
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1962
72.0%
Other Punctuation327
 
12.0%
Dash Punctuation218
 
8.0%
Uppercase Letter109
 
4.0%
Math Symbol109
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01105
56.3%
2408
 
20.8%
1313
 
16.0%
4113
 
5.8%
98
 
0.4%
57
 
0.4%
75
 
0.3%
32
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:327
100.0%
Dash Punctuation
ValueCountFrequency (%)
-218
100.0%
Uppercase Letter
ValueCountFrequency (%)
T109
100.0%
Math Symbol
ValueCountFrequency (%)
+109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2616
96.0%
Latin109
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01105
42.2%
2408
 
15.6%
:327
 
12.5%
1313
 
12.0%
-218
 
8.3%
4113
 
4.3%
+109
 
4.2%
98
 
0.3%
57
 
0.3%
75
 
0.2%
Other values (2)3
 
0.1%
Latin
ValueCountFrequency (%)
T109
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2725
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01105
40.6%
2408
 
15.0%
:327
 
12.0%
1313
 
11.5%
-218
 
8.0%
4113
 
4.1%
T109
 
4.0%
+109
 
4.0%
98
 
0.3%
57
 
0.3%
Other values (3)8
 
0.3%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)32.7%
Missing5
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean40.85576923
Minimum4
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:37.282380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q121.5
median43
Q355.25
95-th percentile88.35
Maximum180
Range176
Interquartile range (IQR)33.75

Descriptive statistics

Standard deviation28.53252896
Coefficient of variation (CV)0.6983720904
Kurtosis6.009140018
Mean40.85576923
Median Absolute Deviation (MAD)17
Skewness1.916323579
Sum4249
Variance814.1052091
MonotonicityNot monotonic
2022-09-04T23:39:37.362818image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4517
15.6%
2312
 
11.0%
6012
 
11.0%
208
 
7.3%
304
 
3.7%
104
 
3.7%
584
 
3.7%
1203
 
2.8%
373
 
2.8%
153
 
2.8%
Other values (24)34
31.2%
(Missing)5
 
4.6%
ValueCountFrequency (%)
41
 
0.9%
52
 
1.8%
72
 
1.8%
104
3.7%
113
 
2.8%
122
 
1.8%
153
 
2.8%
181
 
0.9%
208
7.3%
221
 
0.9%
ValueCountFrequency (%)
1801
 
0.9%
1301
 
0.9%
1203
 
2.8%
901
 
0.9%
791
 
0.9%
6012
11.0%
584
 
3.7%
571
 
0.9%
562
 
1.8%
553
 
2.8%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct30
Distinct (%)100.0%
Missing79
Missing (%)72.5%
Memory size1000.0 B
<p>Ballerina Neveah arrives at Chicago's famed Archer School to find cruel new rivals — and the disturbing truth behind her surprise acceptance.</p><p><br /> </p>
 
1
<p>An old man wants to see his wife smile one more time before he takes his last breath.</p>
 
1
<p>Contestants are quizzed on their English and Botany knowledge as they race towards the second elimination point.  </p>
 
1
<p>Mr. Jan Sport and Mr. Barry-Thunderf*ck sit down with Mr. Royale to chat about how they met their queens, how their queens are making it through Covid, and some special talents of their own!</p>
 
1
<p>Janejira's death has been concluded as a case of suicide. But a lot are still seeking justice for her. And the more you find the truth, the riskier it becomes. Yet this makes Tan and Bun's relationship even closer.</p>
 
1
Other values (25)
25 

Length

Max length221
Median length163.5
Mean length157.6
Min length92

Characters and Unicode

Total characters4728
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row<p>West reveals more about his past while Shatter Squad licks their wounds. Zero gives the team one final taunt. </p>
2nd row<p>Hilda's essay about her close encounter with a troll wins her the chance to tag along with Trolberg's new head of the safety patrol, Erik Ahlberg.</p>
3rd row<p>A quest to uncover secret information about Ahlberg leads Hilda on a high-seas adventure with the Wood Man that lands them in a boatload of trouble.</p>
4th row<p>After Hilda and Frida come across a magical portal at the library, they must team up with the librarian in a race against time to find a missing book.</p>
5th row<p>David confronts his many fears when he stumbles into a ferocious battle during an overnight Sparrow Scouts camping trip with Hilda and Frida.</p>

Common Values

ValueCountFrequency (%)
<p>Ballerina Neveah arrives at Chicago's famed Archer School to find cruel new rivals — and the disturbing truth behind her surprise acceptance.</p><p><br /> </p>1
 
0.9%
<p>An old man wants to see his wife smile one more time before he takes his last breath.</p>1
 
0.9%
<p>Contestants are quizzed on their English and Botany knowledge as they race towards the second elimination point.  </p>1
 
0.9%
<p>Mr. Jan Sport and Mr. Barry-Thunderf*ck sit down with Mr. Royale to chat about how they met their queens, how their queens are making it through Covid, and some special talents of their own!</p>1
 
0.9%
<p>Janejira's death has been concluded as a case of suicide. But a lot are still seeking justice for her. And the more you find the truth, the riskier it becomes. Yet this makes Tan and Bun's relationship even closer.</p>1
 
0.9%
<p>Everything reaches a turning point on the last night of "Ripper," as the dancers pull off a jaw-dropping finale and shocking secrets are revealed.</p>1
 
0.9%
<p>The dancers step up with a viral video to save the school from the expose's fallout. Armed with new evidence, Officer Cruz makes an arrest.</p><p><br /> </p>1
 
0.9%
<p>A photo shoot sheds new light on problems within the group. Neveah pays a price with Madame for talking to the press. Cassie's condition takes a turn.</p><p><br /> </p>1
 
0.9%
<p>Neveah, June and Bette's undercover sting to catch a predator goes sideways. Mixing business with pleasure puts Madame's reign at risk.</p><p><br /> </p>1
 
0.9%
<p>A music video audition promises a big break for a lucky few. Shane and Bette flirt with new love interests, but June has a traumatic encounter.</p><p><br /> </p>1
 
0.9%
Other values (20)20
 
18.3%
(Missing)79
72.5%

Length

2022-09-04T23:39:37.456928image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a33
 
4.2%
the29
 
3.7%
and29
 
3.7%
to23
 
3.0%
with14
 
1.8%
of14
 
1.8%
p11
 
1.4%
11
 
1.4%
for10
 
1.3%
new8
 
1.0%
Other values (446)596
76.6%

Most occurring characters

ValueCountFrequency (%)
738
15.6%
e417
 
8.8%
a319
 
6.7%
t295
 
6.2%
s257
 
5.4%
i251
 
5.3%
o245
 
5.2%
r242
 
5.1%
n239
 
5.1%
h157
 
3.3%
Other values (52)1568
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3503
74.1%
Space Separator749
 
15.8%
Math Symbol174
 
3.7%
Other Punctuation149
 
3.2%
Uppercase Letter138
 
2.9%
Dash Punctuation15
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e417
11.9%
a319
 
9.1%
t295
 
8.4%
s257
 
7.3%
i251
 
7.2%
o245
 
7.0%
r242
 
6.9%
n239
 
6.8%
h157
 
4.5%
p140
 
4.0%
Other values (16)941
26.9%
Uppercase Letter
ValueCountFrequency (%)
A15
10.9%
T14
 
10.1%
H13
 
9.4%
B12
 
8.7%
R9
 
6.5%
S9
 
6.5%
F8
 
5.8%
C8
 
5.8%
M8
 
5.8%
J7
 
5.1%
Other values (12)35
25.4%
Other Punctuation
ValueCountFrequency (%)
/48
32.2%
.45
30.2%
,32
21.5%
'18
 
12.1%
!2
 
1.3%
"2
 
1.3%
:1
 
0.7%
*1
 
0.7%
Space Separator
ValueCountFrequency (%)
738
98.5%
 11
 
1.5%
Math Symbol
ValueCountFrequency (%)
>87
50.0%
<87
50.0%
Dash Punctuation
ValueCountFrequency (%)
-12
80.0%
3
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3641
77.0%
Common1087
 
23.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e417
 
11.5%
a319
 
8.8%
t295
 
8.1%
s257
 
7.1%
i251
 
6.9%
o245
 
6.7%
r242
 
6.6%
n239
 
6.6%
h157
 
4.3%
p140
 
3.8%
Other values (38)1079
29.6%
Common
ValueCountFrequency (%)
738
67.9%
>87
 
8.0%
<87
 
8.0%
/48
 
4.4%
.45
 
4.1%
,32
 
2.9%
'18
 
1.7%
-12
 
1.1%
 11
 
1.0%
3
 
0.3%
Other values (4)6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII4714
99.7%
None11
 
0.2%
Punctuation3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
738
15.7%
e417
 
8.8%
a319
 
6.8%
t295
 
6.3%
s257
 
5.5%
i251
 
5.3%
o245
 
5.2%
r242
 
5.1%
n239
 
5.1%
h157
 
3.3%
Other values (50)1554
33.0%
None
ValueCountFrequency (%)
 11
100.0%
Punctuation
ValueCountFrequency (%)
3
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5
Distinct (%)45.5%
Missing98
Missing (%)89.9%
Memory size1000.0 B
6.7
7.0
7.3
6.8
10.0

Length

Max length4
Median length3
Mean length3.090909091
Min length3

Characters and Unicode

Total characters34
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st row7.3
2nd row6.8
3rd row7.0
4th row7.3
5th row7.0

Common Values

ValueCountFrequency (%)
6.74
 
3.7%
7.03
 
2.8%
7.32
 
1.8%
6.81
 
0.9%
10.01
 
0.9%
(Missing)98
89.9%

Length

2022-09-04T23:39:37.538935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:37.742734image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
6.74
36.4%
7.03
27.3%
7.32
18.2%
6.81
 
9.1%
10.01
 
9.1%

Most occurring characters

ValueCountFrequency (%)
.11
32.4%
79
26.5%
65
14.7%
05
14.7%
32
 
5.9%
81
 
2.9%
11
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number23
67.6%
Other Punctuation11
32.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
79
39.1%
65
21.7%
05
21.7%
32
 
8.7%
81
 
4.3%
11
 
4.3%
Other Punctuation
ValueCountFrequency (%)
.11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common34
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.11
32.4%
79
26.5%
65
14.7%
05
14.7%
32
 
5.9%
81
 
2.9%
11
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.11
32.4%
79
26.5%
65
14.7%
05
14.7%
32
 
5.9%
81
 
2.9%
11
 
2.9%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://api.tvmaze.com/episodes/1982403
 
1
https://api.tvmaze.com/episodes/1978780
 
1
https://api.tvmaze.com/episodes/1988055
 
1
https://api.tvmaze.com/episodes/1988054
 
1
https://api.tvmaze.com/episodes/1988053
 
1
Other values (104)
104 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4251
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1982403
2nd rowhttps://api.tvmaze.com/episodes/1982404
3rd rowhttps://api.tvmaze.com/episodes/2140387
4th rowhttps://api.tvmaze.com/episodes/1945592
5th rowhttps://api.tvmaze.com/episodes/2065442

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19824031
 
0.9%
https://api.tvmaze.com/episodes/19787801
 
0.9%
https://api.tvmaze.com/episodes/19880551
 
0.9%
https://api.tvmaze.com/episodes/19880541
 
0.9%
https://api.tvmaze.com/episodes/19880531
 
0.9%
https://api.tvmaze.com/episodes/19880521
 
0.9%
https://api.tvmaze.com/episodes/19878081
 
0.9%
https://api.tvmaze.com/episodes/19873251
 
0.9%
https://api.tvmaze.com/episodes/19873241
 
0.9%
https://api.tvmaze.com/episodes/19873231
 
0.9%
Other values (99)99
90.8%

Length

2022-09-04T23:39:37.813735image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19824031
 
0.9%
https://api.tvmaze.com/episodes/19860231
 
0.9%
https://api.tvmaze.com/episodes/21403871
 
0.9%
https://api.tvmaze.com/episodes/19455921
 
0.9%
https://api.tvmaze.com/episodes/20654421
 
0.9%
https://api.tvmaze.com/episodes/20714771
 
0.9%
https://api.tvmaze.com/episodes/20714781
 
0.9%
https://api.tvmaze.com/episodes/20802251
 
0.9%
https://api.tvmaze.com/episodes/19773221
 
0.9%
https://api.tvmaze.com/episodes/20030961
 
0.9%
Other values (99)99
90.8%

Most occurring characters

ValueCountFrequency (%)
/436
 
10.3%
p327
 
7.7%
s327
 
7.7%
e327
 
7.7%
t327
 
7.7%
o218
 
5.1%
a218
 
5.1%
i218
 
5.1%
.218
 
5.1%
m218
 
5.1%
Other values (16)1417
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2725
64.1%
Other Punctuation763
 
17.9%
Decimal Number763
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p327
12.0%
s327
12.0%
e327
12.0%
t327
12.0%
o218
8.0%
a218
8.0%
i218
8.0%
m218
8.0%
h109
 
4.0%
d109
 
4.0%
Other values (3)327
12.0%
Decimal Number
ValueCountFrequency (%)
1123
16.1%
9118
15.5%
793
12.2%
885
11.1%
278
10.2%
059
7.7%
555
7.2%
652
6.8%
450
6.6%
350
6.6%
Other Punctuation
ValueCountFrequency (%)
/436
57.1%
.218
28.6%
:109
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2725
64.1%
Common1526
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/436
28.6%
.218
14.3%
1123
 
8.1%
9118
 
7.7%
:109
 
7.1%
793
 
6.1%
885
 
5.6%
278
 
5.1%
059
 
3.9%
555
 
3.6%
Other values (3)152
 
10.0%
Latin
ValueCountFrequency (%)
p327
12.0%
s327
12.0%
e327
12.0%
t327
12.0%
o218
8.0%
a218
8.0%
i218
8.0%
m218
8.0%
h109
 
4.0%
d109
 
4.0%
Other values (3)327
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/436
 
10.3%
p327
 
7.7%
s327
 
7.7%
e327
 
7.7%
t327
 
7.7%
o218
 
5.1%
a218
 
5.1%
i218
 
5.1%
.218
 
5.1%
m218
 
5.1%
Other values (16)1417
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct61
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43262.95413
Minimum802
Maximum63310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:37.893293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile15250
Q135597
median50752
Q352524
95-th percentile60156
Maximum63310
Range62508
Interquartile range (IQR)16927

Descriptive statistics

Standard deviation14654.74005
Coefficient of variation (CV)0.3387364629
Kurtosis0.3515214918
Mean43262.95413
Median Absolute Deviation (MAD)6695
Skewness-1.096470349
Sum4715662
Variance214761406.1
MonotonicityNot monotonic
2022-09-04T23:39:37.982220image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2591013
 
11.9%
4329310
 
9.2%
525248
 
7.3%
524795
 
4.6%
519545
 
4.6%
601565
 
4.6%
549963
 
2.8%
152502
 
1.8%
521592
 
1.8%
521082
 
1.8%
Other values (51)54
49.5%
ValueCountFrequency (%)
8021
0.9%
25041
0.9%
60901
0.9%
61461
0.9%
108211
0.9%
152502
1.8%
174471
0.9%
175841
0.9%
189711
0.9%
224731
0.9%
ValueCountFrequency (%)
633101
 
0.9%
617551
 
0.9%
601565
4.6%
588211
 
0.9%
584261
 
0.9%
583671
 
0.9%
570091
 
0.9%
568481
 
0.9%
566551
 
0.9%
550191
 
0.9%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct61
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://www.tvmaze.com/shows/25910/hilda
13 
https://www.tvmaze.com/shows/43293/tiny-pretty-things
10 
https://www.tvmaze.com/shows/52524/forever-love
https://www.tvmaze.com/shows/52479/beauty-and-the-boss
 
5
https://www.tvmaze.com/shows/51954/the-runner
 
5
Other values (56)
68 

Length

Max length67
Median length57
Mean length48.58715596
Min length39

Characters and Unicode

Total characters5296
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)44.0%

Sample

1st rowhttps://www.tvmaze.com/shows/52181/volk
2nd rowhttps://www.tvmaze.com/shows/52181/volk
3rd rowhttps://www.tvmaze.com/shows/56655/going-seventeen
4th rowhttps://www.tvmaze.com/shows/50916/my-little-invisible-being
5th rowhttps://www.tvmaze.com/shows/54610/the-wonderland-of-ten-thousands

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/25910/hilda13
 
11.9%
https://www.tvmaze.com/shows/43293/tiny-pretty-things10
 
9.2%
https://www.tvmaze.com/shows/52524/forever-love8
 
7.3%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
4.6%
https://www.tvmaze.com/shows/51954/the-runner5
 
4.6%
https://www.tvmaze.com/shows/60156/efsane-t5
 
4.6%
https://www.tvmaze.com/shows/54996/the-silent-criminal3
 
2.8%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
1.8%
https://www.tvmaze.com/shows/52159/to-love2
 
1.8%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
1.8%
Other values (51)54
49.5%

Length

2022-09-04T23:39:38.077896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/25910/hilda13
 
11.9%
https://www.tvmaze.com/shows/43293/tiny-pretty-things10
 
9.2%
https://www.tvmaze.com/shows/52524/forever-love8
 
7.3%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
4.6%
https://www.tvmaze.com/shows/51954/the-runner5
 
4.6%
https://www.tvmaze.com/shows/60156/efsane-t5
 
4.6%
https://www.tvmaze.com/shows/54996/the-silent-criminal3
 
2.8%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
1.8%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
1.8%
https://www.tvmaze.com/shows/52181/volk2
 
1.8%
Other values (51)54
49.5%

Most occurring characters

ValueCountFrequency (%)
/545
 
10.3%
t460
 
8.7%
w450
 
8.5%
s400
 
7.6%
h291
 
5.5%
o291
 
5.5%
e285
 
5.4%
m241
 
4.6%
.218
 
4.1%
a202
 
3.8%
Other values (30)1913
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3718
70.2%
Other Punctuation872
 
16.5%
Decimal Number545
 
10.3%
Dash Punctuation161
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t460
12.4%
w450
12.1%
s400
10.8%
h291
 
7.8%
o291
 
7.8%
e285
 
7.7%
m241
 
6.5%
a202
 
5.4%
v142
 
3.8%
c136
 
3.7%
Other values (16)820
22.1%
Decimal Number
ValueCountFrequency (%)
5107
19.6%
279
14.5%
466
12.1%
159
10.8%
955
10.1%
050
9.2%
641
 
7.5%
339
 
7.2%
725
 
4.6%
824
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/545
62.5%
.218
 
25.0%
:109
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3718
70.2%
Common1578
29.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t460
12.4%
w450
12.1%
s400
10.8%
h291
 
7.8%
o291
 
7.8%
e285
 
7.7%
m241
 
6.5%
a202
 
5.4%
v142
 
3.8%
c136
 
3.7%
Other values (16)820
22.1%
Common
ValueCountFrequency (%)
/545
34.5%
.218
 
13.8%
-161
 
10.2%
:109
 
6.9%
5107
 
6.8%
279
 
5.0%
466
 
4.2%
159
 
3.7%
955
 
3.5%
050
 
3.2%
Other values (4)129
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII5296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/545
 
10.3%
t460
 
8.7%
w450
 
8.5%
s400
 
7.6%
h291
 
5.5%
o291
 
5.5%
e285
 
5.4%
m241
 
4.6%
.218
 
4.1%
a202
 
3.8%
Other values (30)1913
36.1%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct61
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Hilda
13 
Tiny Pretty Things
10 
Forever Love
Beauty and the Boss
 
5
The Runner
 
5
Other values (56)
68 

Length

Max length33
Median length22
Mean length13.70642202
Min length4

Characters and Unicode

Total characters1494
Distinct characters89
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)44.0%

Sample

1st rowВолк
2nd rowВолк
3rd rowGoing Seventeen
4th rowMy Little Invisible Being
5th rowThe Wonderland of Ten Thousands

Common Values

ValueCountFrequency (%)
Hilda13
 
11.9%
Tiny Pretty Things10
 
9.2%
Forever Love8
 
7.3%
Beauty and the Boss5
 
4.6%
The Runner5
 
4.6%
Efsane T5
 
4.6%
The Silent Criminal3
 
2.8%
The Young Turks2
 
1.8%
To Love2
 
1.8%
Psych Hunter2
 
1.8%
Other values (51)54
49.5%

Length

2022-09-04T23:39:38.163481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the23
 
8.5%
hilda13
 
4.8%
love12
 
4.4%
pretty10
 
3.7%
things10
 
3.7%
tiny10
 
3.7%
forever8
 
3.0%
of6
 
2.2%
and6
 
2.2%
efsane5
 
1.9%
Other values (130)167
61.9%

Most occurring characters

ValueCountFrequency (%)
161
 
10.8%
e160
 
10.7%
n92
 
6.2%
i78
 
5.2%
a77
 
5.2%
r77
 
5.2%
t71
 
4.8%
o62
 
4.1%
s59
 
3.9%
T56
 
3.7%
Other values (79)601
40.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1071
71.7%
Uppercase Letter250
 
16.7%
Space Separator161
 
10.8%
Other Punctuation7
 
0.5%
Decimal Number5
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e160
14.9%
n92
 
8.6%
i78
 
7.3%
a77
 
7.2%
r77
 
7.2%
t71
 
6.6%
o62
 
5.8%
s59
 
5.5%
h55
 
5.1%
l43
 
4.0%
Other values (40)297
27.7%
Uppercase Letter
ValueCountFrequency (%)
T56
22.4%
B21
 
8.4%
H17
 
6.8%
P17
 
6.8%
L14
 
5.6%
F13
 
5.2%
S12
 
4.8%
C12
 
4.8%
M12
 
4.8%
R12
 
4.8%
Other values (21)64
25.6%
Other Punctuation
ValueCountFrequency (%)
'2
28.6%
.2
28.6%
!2
28.6%
,1
14.3%
Decimal Number
ValueCountFrequency (%)
03
60.0%
31
 
20.0%
21
 
20.0%
Space Separator
ValueCountFrequency (%)
161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1244
83.3%
Common173
 
11.6%
Cyrillic77
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e160
 
12.9%
n92
 
7.4%
i78
 
6.3%
a77
 
6.2%
r77
 
6.2%
t71
 
5.7%
o62
 
5.0%
s59
 
4.7%
T56
 
4.5%
h55
 
4.4%
Other values (41)457
36.7%
Cyrillic
ValueCountFrequency (%)
о9
 
11.7%
р6
 
7.8%
т6
 
7.8%
л6
 
7.8%
к5
 
6.5%
е5
 
6.5%
а5
 
6.5%
В4
 
5.2%
н3
 
3.9%
п3
 
3.9%
Other values (20)25
32.5%
Common
ValueCountFrequency (%)
161
93.1%
03
 
1.7%
'2
 
1.2%
.2
 
1.2%
!2
 
1.2%
31
 
0.6%
21
 
0.6%
,1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1414
94.6%
Cyrillic77
 
5.2%
None3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
161
 
11.4%
e160
 
11.3%
n92
 
6.5%
i78
 
5.5%
a77
 
5.4%
r77
 
5.4%
t71
 
5.0%
o62
 
4.4%
s59
 
4.2%
T56
 
4.0%
Other values (46)521
36.8%
Cyrillic
ValueCountFrequency (%)
о9
 
11.7%
р6
 
7.8%
т6
 
7.8%
л6
 
7.8%
к5
 
6.5%
е5
 
6.5%
а5
 
6.5%
В4
 
5.2%
н3
 
3.9%
п3
 
3.9%
Other values (20)25
32.5%
None
ValueCountFrequency (%)
ø1
33.3%
Ç1
33.3%
ä1
33.3%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Scripted
57 
Animation
19 
Talk Show
10 
Documentary
Reality
Other values (4)

Length

Max length11
Median length8
Mean length8.293577982
Min length4

Characters and Unicode

Total characters904
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowScripted
2nd rowScripted
3rd rowVariety
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted57
52.3%
Animation19
 
17.4%
Talk Show10
 
9.2%
Documentary8
 
7.3%
Reality7
 
6.4%
News3
 
2.8%
Variety2
 
1.8%
Game Show2
 
1.8%
Sports1
 
0.9%

Length

2022-09-04T23:39:38.235489image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:38.311481image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted57
47.1%
animation19
 
15.7%
show12
 
9.9%
talk10
 
8.3%
documentary8
 
6.6%
reality7
 
5.8%
news3
 
2.5%
variety2
 
1.7%
game2
 
1.7%
sports1
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i104
11.5%
t94
10.4%
e79
 
8.7%
S70
 
7.7%
r68
 
7.5%
c65
 
7.2%
p58
 
6.4%
d57
 
6.3%
a48
 
5.3%
n46
 
5.1%
Other values (17)215
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter771
85.3%
Uppercase Letter121
 
13.4%
Space Separator12
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i104
13.5%
t94
12.2%
e79
10.2%
r68
8.8%
c65
8.4%
p58
7.5%
d57
7.4%
a48
6.2%
n46
6.0%
o40
 
5.2%
Other values (8)112
14.5%
Uppercase Letter
ValueCountFrequency (%)
S70
57.9%
A19
 
15.7%
T10
 
8.3%
D8
 
6.6%
R7
 
5.8%
N3
 
2.5%
V2
 
1.7%
G2
 
1.7%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin892
98.7%
Common12
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i104
11.7%
t94
10.5%
e79
 
8.9%
S70
 
7.8%
r68
 
7.6%
c65
 
7.3%
p58
 
6.5%
d57
 
6.4%
a48
 
5.4%
n46
 
5.2%
Other values (16)203
22.8%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i104
11.5%
t94
10.4%
e79
 
8.7%
S70
 
7.7%
r68
 
7.5%
c65
 
7.2%
p58
 
6.4%
d57
 
6.3%
a48
 
5.3%
n46
 
5.1%
Other values (17)215
23.8%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)13.9%
Missing1
Missing (%)0.9%
Memory size1000.0 B
English
42 
Chinese
33 
Russian
Turkish
Norwegian
 
4
Other values (10)
15 

Length

Max length10
Median length7
Mean length7
Min length4

Characters and Unicode

Total characters756
Distinct characters32
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.6%

Sample

1st rowRussian
2nd rowRussian
3rd rowKorean
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English42
38.5%
Chinese33
30.3%
Russian8
 
7.3%
Turkish6
 
5.5%
Norwegian4
 
3.7%
Korean3
 
2.8%
Swedish2
 
1.8%
Thai2
 
1.8%
Arabic2
 
1.8%
Spanish1
 
0.9%
Other values (5)5
 
4.6%

Length

2022-09-04T23:39:38.391412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english42
38.9%
chinese33
30.6%
russian8
 
7.4%
turkish6
 
5.6%
norwegian4
 
3.7%
korean3
 
2.8%
swedish2
 
1.9%
thai2
 
1.9%
arabic2
 
1.9%
spanish1
 
0.9%
Other values (5)5
 
4.6%

Most occurring characters

ValueCountFrequency (%)
i103
13.6%
s101
13.4%
n95
12.6%
h88
11.6%
e78
10.3%
g47
6.2%
E42
5.6%
l42
5.6%
C33
 
4.4%
a25
 
3.3%
Other values (22)102
13.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter648
85.7%
Uppercase Letter108
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i103
15.9%
s101
15.6%
n95
14.7%
h88
13.6%
e78
12.0%
g47
7.3%
l42
6.5%
a25
 
3.9%
u18
 
2.8%
r17
 
2.6%
Other values (10)34
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
E42
38.9%
C33
30.6%
T8
 
7.4%
R8
 
7.4%
N4
 
3.7%
K3
 
2.8%
S3
 
2.8%
L2
 
1.9%
A2
 
1.9%
P1
 
0.9%
Other values (2)2
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin756
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i103
13.6%
s101
13.4%
n95
12.6%
h88
11.6%
e78
10.3%
g47
6.2%
E42
5.6%
l42
5.6%
C33
 
4.4%
a25
 
3.3%
Other values (22)102
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i103
13.6%
s101
13.4%
n95
12.6%
h88
11.6%
e78
10.3%
g47
6.2%
E42
5.6%
l42
5.6%
C33
 
4.4%
a25
 
3.3%
Other values (22)102
13.5%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1000.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
Ended
56 
Running
49 
To Be Determined
 
4

Length

Max length16
Median length5
Mean length6.302752294
Min length5

Characters and Unicode

Total characters687
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended56
51.4%
Running49
45.0%
To Be Determined4
 
3.7%

Length

2022-09-04T23:39:38.463412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:38.535640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ended56
47.9%
running49
41.9%
to4
 
3.4%
be4
 
3.4%
determined4
 
3.4%

Most occurring characters

ValueCountFrequency (%)
n207
30.1%
d116
16.9%
e72
 
10.5%
E56
 
8.2%
i53
 
7.7%
R49
 
7.1%
u49
 
7.1%
g49
 
7.1%
8
 
1.2%
T4
 
0.6%
Other values (6)24
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter562
81.8%
Uppercase Letter117
 
17.0%
Space Separator8
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n207
36.8%
d116
20.6%
e72
 
12.8%
i53
 
9.4%
u49
 
8.7%
g49
 
8.7%
o4
 
0.7%
t4
 
0.7%
r4
 
0.7%
m4
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
E56
47.9%
R49
41.9%
T4
 
3.4%
B4
 
3.4%
D4
 
3.4%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin679
98.8%
Common8
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n207
30.5%
d116
17.1%
e72
 
10.6%
E56
 
8.2%
i53
 
7.8%
R49
 
7.2%
u49
 
7.2%
g49
 
7.2%
T4
 
0.6%
o4
 
0.6%
Other values (5)20
 
2.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n207
30.1%
d116
16.9%
e72
 
10.5%
E56
 
8.2%
i53
 
7.7%
R49
 
7.1%
u49
 
7.1%
g49
 
7.1%
8
 
1.2%
T4
 
0.6%
Other values (6)24
 
3.5%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)27.6%
Missing22
Missing (%)20.2%
Infinite0
Infinite (%)0.0%
Mean40.37931034
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:38.602777image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10
Q121
median37
Q351
95-th percentile111
Maximum180
Range175
Interquartile range (IQR)30

Descriptive statistics

Standard deviation29.78146816
Coefficient of variation (CV)0.7375427641
Kurtosis6.2122035
Mean40.37931034
Median Absolute Deviation (MAD)15
Skewness2.098196683
Sum3513
Variance886.935846
MonotonicityNot monotonic
2022-09-04T23:39:38.677778image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4516
14.7%
6014
12.8%
2413
11.9%
208
 
7.3%
104
 
3.7%
304
 
3.7%
153
 
2.8%
373
 
2.8%
1203
 
2.8%
512
 
1.8%
Other values (14)17
15.6%
(Missing)22
20.2%
ValueCountFrequency (%)
52
 
1.8%
72
 
1.8%
104
3.7%
111
 
0.9%
121
 
0.9%
153
 
2.8%
161
 
0.9%
208
7.3%
221
 
0.9%
231
 
0.9%
ValueCountFrequency (%)
1801
 
0.9%
1301
 
0.9%
1203
 
2.8%
901
 
0.9%
6014
12.8%
551
 
0.9%
512
 
1.8%
501
 
0.9%
4516
14.7%
401
 
0.9%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct30
Distinct (%)27.8%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean40.12962963
Minimum4
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:38.761777image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.35
Q120
median39
Q357
95-th percentile79.5
Maximum181
Range177
Interquartile range (IQR)37

Descriptive statistics

Standard deviation28.17073864
Coefficient of variation (CV)0.7019934872
Kurtosis6.483818673
Mean40.12962963
Median Absolute Deviation (MAD)18
Skewness1.979408387
Sum4334
Variance793.5905157
MonotonicityNot monotonic
2022-09-04T23:39:38.848654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4516
14.7%
2413
11.9%
6012
11.0%
5710
 
9.2%
208
 
7.3%
105
 
4.6%
255
 
4.6%
504
 
3.7%
303
 
2.8%
373
 
2.8%
Other values (20)29
26.6%
ValueCountFrequency (%)
41
 
0.9%
52
 
1.8%
72
 
1.8%
91
 
0.9%
105
4.6%
112
 
1.8%
122
 
1.8%
141
 
0.9%
153
2.8%
161
 
0.9%
ValueCountFrequency (%)
1811
 
0.9%
1301
 
0.9%
1203
 
2.8%
901
 
0.9%
6012
11.0%
591
 
0.9%
581
 
0.9%
5710
9.2%
531
 
0.9%
504
 
3.7%

_embedded.show.premiered
Categorical

HIGH CORRELATION

Distinct47
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2020-12-14
30 
2018-09-21
13 
2020-11-23
2020-11-16
 
5
2020-11-09
 
4
Other values (42)
50 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1090
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)33.9%

Sample

1st row2020-12-07
2nd row2020-12-07
3rd row2017-06-12
4th row2020-10-05
5th row2018-03-30

Common Values

ValueCountFrequency (%)
2020-12-1430
27.5%
2018-09-2113
 
11.9%
2020-11-237
 
6.4%
2020-11-165
 
4.6%
2020-11-094
 
3.7%
2020-12-074
 
3.7%
2020-11-303
 
2.8%
2013-12-242
 
1.8%
2020-11-192
 
1.8%
2020-12-132
 
1.8%
Other values (37)37
33.9%

Length

2022-09-04T23:39:38.931409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1430
27.5%
2018-09-2113
 
11.9%
2020-11-237
 
6.4%
2020-11-165
 
4.6%
2020-11-094
 
3.7%
2020-12-074
 
3.7%
2020-11-303
 
2.8%
2020-11-192
 
1.8%
2020-12-132
 
1.8%
2013-12-242
 
1.8%
Other values (37)37
33.9%

Most occurring characters

ValueCountFrequency (%)
0251
23.0%
2247
22.7%
-218
20.0%
1213
19.5%
440
 
3.7%
936
 
3.3%
325
 
2.3%
824
 
2.2%
715
 
1.4%
612
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number872
80.0%
Dash Punctuation218
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0251
28.8%
2247
28.3%
1213
24.4%
440
 
4.6%
936
 
4.1%
325
 
2.9%
824
 
2.8%
715
 
1.7%
612
 
1.4%
59
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
-218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1090
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0251
23.0%
2247
22.7%
-218
20.0%
1213
19.5%
440
 
3.7%
936
 
3.3%
325
 
2.3%
824
 
2.2%
715
 
1.4%
612
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0251
23.0%
2247
22.7%
-218
20.0%
1213
19.5%
440
 
3.7%
936
 
3.3%
325
 
2.3%
824
 
2.2%
715
 
1.4%
612
 
1.1%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)25.0%
Missing53
Missing (%)48.6%
Memory size1000.0 B
2020-12-14
24 
2021-01-05
2021-01-18
2020-12-28
2020-12-22
 
2
Other values (9)
12 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters560
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)10.7%

Sample

1st row2020-12-28
2nd row2020-12-28
3rd row2020-12-22
4th row2020-12-22
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2020-12-1424
22.0%
2021-01-058
 
7.3%
2021-01-187
 
6.4%
2020-12-283
 
2.8%
2020-12-222
 
1.8%
2020-12-302
 
1.8%
2020-12-162
 
1.8%
2020-12-232
 
1.8%
2020-12-241
 
0.9%
2021-02-221
 
0.9%
Other values (4)4
 
3.7%
(Missing)53
48.6%

Length

2022-09-04T23:39:39.000600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1424
42.9%
2021-01-058
 
14.3%
2021-01-187
 
12.5%
2020-12-283
 
5.4%
2020-12-222
 
3.6%
2020-12-302
 
3.6%
2020-12-162
 
3.6%
2020-12-232
 
3.6%
2020-12-241
 
1.8%
2021-02-221
 
1.8%
Other values (4)4
 
7.1%

Most occurring characters

ValueCountFrequency (%)
2165
29.5%
0122
21.8%
-112
20.0%
1108
19.3%
425
 
4.5%
812
 
2.1%
58
 
1.4%
34
 
0.7%
63
 
0.5%
71
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number448
80.0%
Dash Punctuation112
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2165
36.8%
0122
27.2%
1108
24.1%
425
 
5.6%
812
 
2.7%
58
 
1.8%
34
 
0.9%
63
 
0.7%
71
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2165
29.5%
0122
21.8%
-112
20.0%
1108
19.3%
425
 
4.5%
812
 
2.1%
58
 
1.4%
34
 
0.7%
63
 
0.5%
71
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2165
29.5%
0122
21.8%
-112
20.0%
1108
19.3%
425
 
4.5%
812
 
2.1%
58
 
1.4%
34
 
0.7%
63
 
0.5%
71
 
0.2%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct56
Distinct (%)58.3%
Missing13
Missing (%)11.9%
Memory size1000.0 B
https://www.netflix.com/title/80115346
13 
https://www.netflix.com/title/81017308
10 
https://v.qq.com/detail/m/mzc00200dnvb1wh.html
https://programme.mytvsuper.com/tc/130336/
 
5
https://www.iqiyi.com/a_je0t80m6td.html
 
3
Other values (51)
57 

Length

Max length105
Median length86
Mean length47.55208333
Min length18

Characters and Unicode

Total characters4565
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)46.9%

Sample

1st rowhttps://premier.one/show/12339
2nd rowhttps://premier.one/show/12339
3rd rowhttps://www.bilibili.com/bangumi/media/md28229943/
4th rowhttps://v.qq.com/detail/5/5cuf8ahvxvm2587.html
5th rowhttps://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef

Common Values

ValueCountFrequency (%)
https://www.netflix.com/title/8011534613
 
11.9%
https://www.netflix.com/title/8101730810
 
9.2%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html8
 
7.3%
https://programme.mytvsuper.com/tc/130336/5
 
4.6%
https://www.iqiyi.com/a_je0t80m6td.html3
 
2.8%
https://premier.one/show/123392
 
1.8%
https://www.tytnetwork.com2
 
1.8%
https://www.iqiyi.com/a_19rrhskr95.html2
 
1.8%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
1.8%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
1.8%
Other values (46)47
43.1%
(Missing)13
 
11.9%

Length

2022-09-04T23:39:39.084592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com/title/8011534613
 
13.5%
https://www.netflix.com/title/8101730810
 
10.4%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html8
 
8.3%
https://programme.mytvsuper.com/tc/1303365
 
5.2%
https://www.iqiyi.com/a_je0t80m6td.html3
 
3.1%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.1%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.1%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
2.1%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.1%
https://www.tytnetwork.com2
 
2.1%
Other values (46)47
49.0%

Most occurring characters

ValueCountFrequency (%)
t404
 
8.8%
/403
 
8.8%
e231
 
5.1%
w203
 
4.4%
s202
 
4.4%
.202
 
4.4%
h183
 
4.0%
o175
 
3.8%
m166
 
3.6%
i146
 
3.2%
Other values (64)2250
49.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2934
64.3%
Other Punctuation782
 
17.1%
Decimal Number579
 
12.7%
Uppercase Letter175
 
3.8%
Dash Punctuation51
 
1.1%
Math Symbol26
 
0.6%
Connector Punctuation18
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t404
13.8%
e231
 
7.9%
w203
 
6.9%
s202
 
6.9%
h183
 
6.2%
o175
 
6.0%
m166
 
5.7%
i146
 
5.0%
p143
 
4.9%
l129
 
4.4%
Other values (16)952
32.4%
Uppercase Letter
ValueCountFrequency (%)
E21
 
12.0%
B14
 
8.0%
P13
 
7.4%
A13
 
7.4%
D12
 
6.9%
C10
 
5.7%
M10
 
5.7%
T9
 
5.1%
U9
 
5.1%
Z8
 
4.6%
Other values (15)56
32.0%
Decimal Number
ValueCountFrequency (%)
0112
19.3%
1100
17.3%
370
12.1%
864
11.1%
451
8.8%
541
 
7.1%
640
 
6.9%
239
 
6.7%
932
 
5.5%
730
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/403
51.5%
.202
25.8%
:96
 
12.3%
%57
 
7.3%
?12
 
1.5%
&8
 
1.0%
,2
 
0.3%
!1
 
0.1%
#1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=24
92.3%
+2
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
-51
100.0%
Connector Punctuation
ValueCountFrequency (%)
_18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3109
68.1%
Common1456
31.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t404
 
13.0%
e231
 
7.4%
w203
 
6.5%
s202
 
6.5%
h183
 
5.9%
o175
 
5.6%
m166
 
5.3%
i146
 
4.7%
p143
 
4.6%
l129
 
4.1%
Other values (41)1127
36.2%
Common
ValueCountFrequency (%)
/403
27.7%
.202
13.9%
0112
 
7.7%
1100
 
6.9%
:96
 
6.6%
370
 
4.8%
864
 
4.4%
%57
 
3.9%
-51
 
3.5%
451
 
3.5%
Other values (13)250
17.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII4565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t404
 
8.8%
/403
 
8.8%
e231
 
5.1%
w203
 
4.4%
s202
 
4.4%
.202
 
4.4%
h183
 
4.0%
o175
 
3.8%
m166
 
3.6%
i146
 
3.2%
Other values (64)2250
49.3%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
74 
20:00
25 
10:00
 
2
08:00
 
1
12:00
 
1
Other values (6)
 
6

Length

Max length5
Median length0
Mean length1.605504587
Min length0

Characters and Unicode

Total characters175
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)7.3%

Sample

1st row
2nd row
3rd row08:00
4th row12:00
5th row10:00

Common Values

ValueCountFrequency (%)
74
67.9%
20:0025
 
22.9%
10:002
 
1.8%
08:001
 
0.9%
12:001
 
0.9%
06:001
 
0.9%
17:351
 
0.9%
00:001
 
0.9%
19:001
 
0.9%
20:151
 
0.9%

Length

2022-09-04T23:39:39.171522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0025
71.4%
10:002
 
5.7%
08:001
 
2.9%
12:001
 
2.9%
06:001
 
2.9%
17:351
 
2.9%
00:001
 
2.9%
19:001
 
2.9%
20:151
 
2.9%
17:001
 
2.9%

Most occurring characters

ValueCountFrequency (%)
098
56.0%
:35
 
20.0%
227
 
15.4%
17
 
4.0%
72
 
1.1%
52
 
1.1%
81
 
0.6%
61
 
0.6%
31
 
0.6%
91
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number140
80.0%
Other Punctuation35
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
098
70.0%
227
 
19.3%
17
 
5.0%
72
 
1.4%
52
 
1.4%
81
 
0.7%
61
 
0.7%
31
 
0.7%
91
 
0.7%
Other Punctuation
ValueCountFrequency (%)
:35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
098
56.0%
:35
 
20.0%
227
 
15.4%
17
 
4.0%
72
 
1.1%
52
 
1.1%
81
 
0.6%
61
 
0.6%
31
 
0.6%
91
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
098
56.0%
:35
 
20.0%
227
 
15.4%
17
 
4.0%
72
 
1.1%
52
 
1.1%
81
 
0.6%
61
 
0.6%
31
 
0.6%
91
 
0.6%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1000.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)15.4%
Missing83
Missing (%)76.1%
Memory size1000.0 B
7.4
13 
6.7
10 
7.2
7.5
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters78
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st row7.4
2nd row7.4
3rd row7.4
4th row7.4
5th row7.4

Common Values

ValueCountFrequency (%)
7.413
 
11.9%
6.710
 
9.2%
7.22
 
1.8%
7.51
 
0.9%
(Missing)83
76.1%

Length

2022-09-04T23:39:39.243874image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:39.315493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
7.413
50.0%
6.710
38.5%
7.22
 
7.7%
7.51
 
3.8%

Most occurring characters

ValueCountFrequency (%)
726
33.3%
.26
33.3%
413
16.7%
610
 
12.8%
22
 
2.6%
51
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number52
66.7%
Other Punctuation26
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
726
50.0%
413
25.0%
610
 
19.2%
22
 
3.8%
51
 
1.9%
Other Punctuation
ValueCountFrequency (%)
.26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common78
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
726
33.3%
.26
33.3%
413
16.7%
610
 
12.8%
22
 
2.6%
51
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII78
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
726
33.3%
.26
33.3%
413
16.7%
610
 
12.8%
22
 
2.6%
51
 
1.3%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct41
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.03669725
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:39.388471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q115
median27
Q379
95-th percentile90
Maximum95
Range94
Interquartile range (IQR)64

Descriptive statistics

Standard deviation31.34542515
Coefficient of variation (CV)0.782917356
Kurtosis-1.24407771
Mean40.03669725
Median Absolute Deviation (MAD)13
Skewness0.6192768818
Sum4364
Variance982.5356779
MonotonicityNot monotonic
2022-09-04T23:39:39.475404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
9013
 
11.9%
8412
 
11.0%
309
 
8.3%
157
 
6.4%
206
 
5.5%
145
 
4.6%
25
 
4.6%
274
 
3.7%
264
 
3.7%
293
 
2.8%
Other values (31)41
37.6%
ValueCountFrequency (%)
11
 
0.9%
25
4.6%
32
 
1.8%
42
 
1.8%
62
 
1.8%
71
 
0.9%
81
 
0.9%
111
 
0.9%
121
 
0.9%
131
 
0.9%
ValueCountFrequency (%)
951
 
0.9%
9013
11.9%
871
 
0.9%
8412
11.0%
791
 
0.9%
761
 
0.9%
721
 
0.9%
701
 
0.9%
691
 
0.9%
631
 
0.9%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct33
Distinct (%)30.6%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean134.9259259
Minimum1
Maximum518
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:39.664960image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median103
Q3222
95-th percentile428
Maximum518
Range517
Interquartile range (IQR)201

Descriptive statistics

Standard deviation148.2484467
Coefficient of variation (CV)1.098739517
Kurtosis0.1043293679
Mean134.9259259
Median Absolute Deviation (MAD)95.5
Skewness1.090962508
Sum14572
Variance21977.60194
MonotonicityNot monotonic
2022-09-04T23:39:39.749169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
123
21.1%
2116
14.7%
10412
11.0%
676
 
5.5%
4285
 
4.6%
2225
 
4.6%
2625
 
4.6%
1184
 
3.7%
152
 
1.8%
322
 
1.8%
Other values (23)28
25.7%
ValueCountFrequency (%)
123
21.1%
152
 
1.8%
2116
14.7%
301
 
0.9%
322
 
1.8%
401
 
0.9%
511
 
0.9%
676
 
5.5%
991
 
0.9%
1021
 
0.9%
ValueCountFrequency (%)
5182
 
1.8%
5161
 
0.9%
4981
 
0.9%
4285
4.6%
4131
 
0.9%
3792
 
1.8%
3681
 
0.9%
3671
 
0.9%
3471
 
0.9%
3272
 
1.8%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION

Distinct33
Distinct (%)30.6%
Missing1
Missing (%)0.9%
Memory size1000.0 B
Netflix
23 
YouTube
16 
Tencent QQ
12 
iQIYI
TVB Anywhere
Other values (28)
46 

Length

Max length20
Median length17
Mean length7.814814815
Min length3

Characters and Unicode

Total characters844
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)16.7%

Sample

1st rowPremier
2nd rowPremier
3rd rowV LIVE
4th rowBilibili
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
Netflix23
21.1%
YouTube16
14.7%
Tencent QQ12
11.0%
iQIYI6
 
5.5%
TVB Anywhere5
 
4.6%
BluTV5
 
4.6%
myTV SUPER5
 
4.6%
Youku4
 
3.7%
WWE Network2
 
1.8%
Rooster Teeth2
 
1.8%
Other values (23)28
25.7%

Length

2022-09-04T23:39:39.836247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
netflix23
15.6%
youtube16
 
10.9%
tencent12
 
8.2%
qq12
 
8.2%
iqiyi6
 
4.1%
blutv5
 
3.4%
super5
 
3.4%
mytv5
 
3.4%
anywhere5
 
3.4%
tvb5
 
3.4%
Other values (36)53
36.1%

Most occurring characters

ValueCountFrequency (%)
e103
 
12.2%
T54
 
6.4%
u50
 
5.9%
t49
 
5.8%
i44
 
5.2%
39
 
4.6%
o37
 
4.4%
l36
 
4.3%
n31
 
3.7%
Q30
 
3.6%
Other values (36)371
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter543
64.3%
Uppercase Letter256
30.3%
Space Separator39
 
4.6%
Decimal Number4
 
0.5%
Math Symbol2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e103
19.0%
u50
 
9.2%
t49
 
9.0%
i44
 
8.1%
o37
 
6.8%
l36
 
6.6%
n31
 
5.7%
f25
 
4.6%
x23
 
4.2%
b20
 
3.7%
Other values (12)125
23.0%
Uppercase Letter
ValueCountFrequency (%)
T54
21.1%
Q30
11.7%
N28
10.9%
V26
10.2%
Y26
10.2%
I13
 
5.1%
P13
 
5.1%
B12
 
4.7%
R10
 
3.9%
W8
 
3.1%
Other values (10)36
14.1%
Decimal Number
ValueCountFrequency (%)
22
50.0%
32
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin799
94.7%
Common45
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e103
 
12.9%
T54
 
6.8%
u50
 
6.3%
t49
 
6.1%
i44
 
5.5%
o37
 
4.6%
l36
 
4.5%
n31
 
3.9%
Q30
 
3.8%
N28
 
3.5%
Other values (32)337
42.2%
Common
ValueCountFrequency (%)
39
86.7%
+2
 
4.4%
22
 
4.4%
32
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e103
 
12.2%
T54
 
6.4%
u50
 
5.9%
t49
 
5.8%
i44
 
5.2%
39
 
4.6%
o37
 
4.4%
l36
 
4.3%
n31
 
3.7%
Q30
 
3.6%
Other values (36)371
44.0%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)18.0%
Missing59
Missing (%)54.1%
Memory size1000.0 B
China
17 
Hong Kong
10 
United States
Turkey
Russian Federation
Other values (4)

Length

Max length18
Median length13
Mean length8.46
Min length5

Characters and Unicode

Total characters423
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.0%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowKorea, Republic of
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China17
 
15.6%
Hong Kong10
 
9.2%
United States7
 
6.4%
Turkey6
 
5.5%
Russian Federation3
 
2.8%
Norway3
 
2.8%
Korea, Republic of2
 
1.8%
Brazil1
 
0.9%
Germany1
 
0.9%
(Missing)59
54.1%

Length

2022-09-04T23:39:39.919246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:40.008060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
china17
23.0%
hong10
13.5%
kong10
13.5%
united7
9.5%
states7
9.5%
turkey6
 
8.1%
russian3
 
4.1%
federation3
 
4.1%
norway3
 
4.1%
korea2
 
2.7%
Other values (4)6
 
8.1%

Most occurring characters

ValueCountFrequency (%)
n51
 
12.1%
a37
 
8.7%
i33
 
7.8%
e31
 
7.3%
o30
 
7.1%
24
 
5.7%
t24
 
5.7%
g20
 
4.7%
C17
 
4.0%
h17
 
4.0%
Other values (25)139
32.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter325
76.8%
Uppercase Letter72
 
17.0%
Space Separator24
 
5.7%
Other Punctuation2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n51
15.7%
a37
11.4%
i33
10.2%
e31
9.5%
o30
9.2%
t24
7.4%
g20
 
6.2%
h17
 
5.2%
r16
 
4.9%
s13
 
4.0%
Other values (12)53
16.3%
Uppercase Letter
ValueCountFrequency (%)
C17
23.6%
K12
16.7%
H10
13.9%
S7
9.7%
U7
9.7%
T6
 
8.3%
R5
 
6.9%
N3
 
4.2%
F3
 
4.2%
B1
 
1.4%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
,2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin397
93.9%
Common26
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n51
12.8%
a37
 
9.3%
i33
 
8.3%
e31
 
7.8%
o30
 
7.6%
t24
 
6.0%
g20
 
5.0%
C17
 
4.3%
h17
 
4.3%
r16
 
4.0%
Other values (23)121
30.5%
Common
ValueCountFrequency (%)
24
92.3%
,2
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n51
 
12.1%
a37
 
8.7%
i33
 
7.8%
e31
 
7.3%
o30
 
7.1%
24
 
5.7%
t24
 
5.7%
g20
 
4.7%
C17
 
4.0%
h17
 
4.0%
Other values (25)139
32.9%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)18.0%
Missing59
Missing (%)54.1%
Memory size1000.0 B
CN
17 
HK
10 
US
TR
RU
Other values (4)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters100
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.0%

Sample

1st rowRU
2nd rowRU
3rd rowKR
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN17
 
15.6%
HK10
 
9.2%
US7
 
6.4%
TR6
 
5.5%
RU3
 
2.8%
NO3
 
2.8%
KR2
 
1.8%
BR1
 
0.9%
DE1
 
0.9%
(Missing)59
54.1%

Length

2022-09-04T23:39:40.097060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:40.184060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
cn17
34.0%
hk10
20.0%
us7
14.0%
tr6
 
12.0%
ru3
 
6.0%
no3
 
6.0%
kr2
 
4.0%
br1
 
2.0%
de1
 
2.0%

Most occurring characters

ValueCountFrequency (%)
N20
20.0%
C17
17.0%
K12
12.0%
R12
12.0%
H10
10.0%
U10
10.0%
S7
 
7.0%
T6
 
6.0%
O3
 
3.0%
B1
 
1.0%
Other values (2)2
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter100
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N20
20.0%
C17
17.0%
K12
12.0%
R12
12.0%
H10
10.0%
U10
10.0%
S7
 
7.0%
T6
 
6.0%
O3
 
3.0%
B1
 
1.0%
Other values (2)2
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin100
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N20
20.0%
C17
17.0%
K12
12.0%
R12
12.0%
H10
10.0%
U10
10.0%
S7
 
7.0%
T6
 
6.0%
O3
 
3.0%
B1
 
1.0%
Other values (2)2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N20
20.0%
C17
17.0%
K12
12.0%
R12
12.0%
H10
10.0%
U10
10.0%
S7
 
7.0%
T6
 
6.0%
O3
 
3.0%
B1
 
1.0%
Other values (2)2
 
2.0%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)18.0%
Missing59
Missing (%)54.1%
Memory size1000.0 B
Asia/Shanghai
17 
Asia/Hong_Kong
10 
America/New_York
Europe/Istanbul
Asia/Kamchatka
Other values (4)

Length

Max length16
Median length15
Mean length13.76
Min length10

Characters and Unicode

Total characters688
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.0%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Seoul
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai17
 
15.6%
Asia/Hong_Kong10
 
9.2%
America/New_York7
 
6.4%
Europe/Istanbul6
 
5.5%
Asia/Kamchatka3
 
2.8%
Europe/Oslo3
 
2.8%
Asia/Seoul2
 
1.8%
America/Noronha1
 
0.9%
Europe/Busingen1
 
0.9%
(Missing)59
54.1%

Length

2022-09-04T23:39:40.274060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:40.364336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai17
34.0%
asia/hong_kong10
20.0%
america/new_york7
14.0%
europe/istanbul6
 
12.0%
asia/kamchatka3
 
6.0%
europe/oslo3
 
6.0%
asia/seoul2
 
4.0%
america/noronha1
 
2.0%
europe/busingen1
 
2.0%

Most occurring characters

ValueCountFrequency (%)
a90
13.1%
i58
 
8.4%
/50
 
7.3%
n46
 
6.7%
o44
 
6.4%
s42
 
6.1%
A40
 
5.8%
h38
 
5.5%
g38
 
5.5%
e28
 
4.1%
Other values (20)214
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter504
73.3%
Uppercase Letter117
 
17.0%
Other Punctuation50
 
7.3%
Connector Punctuation17
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a90
17.9%
i58
11.5%
n46
9.1%
o44
8.7%
s42
8.3%
h38
7.5%
g38
7.5%
e28
 
5.6%
r26
 
5.2%
u19
 
3.8%
Other values (8)75
14.9%
Uppercase Letter
ValueCountFrequency (%)
A40
34.2%
S19
16.2%
K13
 
11.1%
E10
 
8.5%
H10
 
8.5%
N8
 
6.8%
Y7
 
6.0%
I6
 
5.1%
O3
 
2.6%
B1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/50
100.0%
Connector Punctuation
ValueCountFrequency (%)
_17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin621
90.3%
Common67
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a90
14.5%
i58
 
9.3%
n46
 
7.4%
o44
 
7.1%
s42
 
6.8%
A40
 
6.4%
h38
 
6.1%
g38
 
6.1%
e28
 
4.5%
r26
 
4.2%
Other values (18)171
27.5%
Common
ValueCountFrequency (%)
/50
74.6%
_17
 
25.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a90
13.1%
i58
 
8.4%
/50
 
7.3%
n46
 
6.7%
o44
 
6.4%
s42
 
6.1%
A40
 
5.8%
h38
 
5.5%
g38
 
5.5%
e28
 
4.1%
Other values (20)214
31.1%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)15.9%
Missing46
Missing (%)42.2%
Memory size1000.0 B
https://www.netflix.com/
23 
https://www.youtube.com
16 
https://v.qq.com/
12 
https://www.iq.com/
https://www.vlive.tv/home
 
1
Other values (5)

Length

Max length30
Median length26
Mean length22.01587302
Min length17

Characters and Unicode

Total characters1387
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)9.5%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://www.youtube.com
5th rowhttps://www.youtube.com

Common Values

ValueCountFrequency (%)
https://www.netflix.com/23
21.1%
https://www.youtube.com16
 
14.7%
https://v.qq.com/12
 
11.0%
https://www.iq.com/6
 
5.5%
https://www.vlive.tv/home1
 
0.9%
https://wetv.vip/1
 
0.9%
https://www.discoveryplus.com/1
 
0.9%
http://www.wowpresentsplus.com1
 
0.9%
https://tv.naver.com/1
 
0.9%
https://www.peacocktv.com/1
 
0.9%
(Missing)46
42.2%

Length

2022-09-04T23:39:40.462413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:40.544730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.netflix.com23
36.5%
https://www.youtube.com16
25.4%
https://v.qq.com12
19.0%
https://www.iq.com6
 
9.5%
https://www.vlive.tv/home1
 
1.6%
https://wetv.vip1
 
1.6%
https://www.discoveryplus.com1
 
1.6%
http://www.wowpresentsplus.com1
 
1.6%
https://tv.naver.com1
 
1.6%
https://www.peacocktv.com1
 
1.6%

Most occurring characters

ValueCountFrequency (%)
/172
12.4%
t170
12.3%
w150
10.8%
.125
 
9.0%
o81
 
5.8%
p68
 
4.9%
s67
 
4.8%
h64
 
4.6%
c64
 
4.6%
:63
 
4.5%
Other values (16)363
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1027
74.0%
Other Punctuation360
 
26.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t170
16.6%
w150
14.6%
o81
 
7.9%
p68
 
6.6%
s67
 
6.5%
h64
 
6.2%
c64
 
6.2%
m62
 
6.0%
e47
 
4.6%
u34
 
3.3%
Other values (13)220
21.4%
Other Punctuation
ValueCountFrequency (%)
/172
47.8%
.125
34.7%
:63
 
17.5%

Most occurring scripts

ValueCountFrequency (%)
Latin1027
74.0%
Common360
 
26.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t170
16.6%
w150
14.6%
o81
 
7.9%
p68
 
6.6%
s67
 
6.5%
h64
 
6.2%
c64
 
6.2%
m62
 
6.0%
e47
 
4.6%
u34
 
3.3%
Other values (13)220
21.4%
Common
ValueCountFrequency (%)
/172
47.8%
.125
34.7%
:63
 
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/172
12.4%
t170
12.3%
w150
10.8%
.125
 
9.0%
o81
 
5.8%
p68
 
4.9%
s67
 
4.8%
h64
 
4.6%
c64
 
4.6%
:63
 
4.5%
Other values (16)363
26.2%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing106
Missing (%)97.2%
Memory size1000.0 B
30282.0
19056.0
6659.0

Length

Max length7
Median length7
Mean length6.666666667
Min length6

Characters and Unicode

Total characters20
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row30282.0
2nd row19056.0
3rd row6659.0

Common Values

ValueCountFrequency (%)
30282.01
 
0.9%
19056.01
 
0.9%
6659.01
 
0.9%
(Missing)106
97.2%

Length

2022-09-04T23:39:40.640722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:40.710721image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
30282.01
33.3%
19056.01
33.3%
6659.01
33.3%

Most occurring characters

ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number17
85.0%
Other Punctuation3
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
29.4%
63
17.6%
22
 
11.8%
92
 
11.8%
52
 
11.8%
31
 
5.9%
81
 
5.9%
11
 
5.9%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
25.0%
.3
15.0%
63
15.0%
22
 
10.0%
92
 
10.0%
52
 
10.0%
31
 
5.0%
81
 
5.0%
11
 
5.0%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct48
Distinct (%)51.1%
Missing15
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean349672.3298
Minimum73246
Maximum408956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:40.779730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum73246
5-th percentile130739
Q1347744.75
median384751
Q3393198
95-th percentile398615
Maximum408956
Range335710
Interquartile range (IQR)45453.25

Descriptive statistics

Standard deviation76903.05999
Coefficient of variation (CV)0.2199289261
Kurtosis6.092899605
Mean349672.3298
Median Absolute Deviation (MAD)12871
Skewness-2.52542579
Sum32869199
Variance5914080635
MonotonicityNot monotonic
2022-09-04T23:39:40.861717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
34964313
 
11.9%
38475110
 
9.2%
3933818
 
7.3%
3934735
 
4.6%
3986155
 
4.6%
3919895
 
4.6%
3923553
 
2.8%
2787932
 
1.8%
3922142
 
1.8%
3923622
 
1.8%
Other values (38)39
35.8%
(Missing)15
 
13.8%
ValueCountFrequency (%)
732461
0.9%
767791
0.9%
788961
0.9%
794291
0.9%
1042711
0.9%
1449911
0.9%
2479561
0.9%
2541191
0.9%
2644581
0.9%
2651931
0.9%
ValueCountFrequency (%)
4089561
 
0.9%
4017901
 
0.9%
3986155
4.6%
3972472
 
1.8%
3946271
 
0.9%
3940451
 
0.9%
3934735
4.6%
3933818
7.3%
3926491
 
0.9%
3923991
 
0.9%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)48.3%
Missing51
Missing (%)46.8%
Memory size1000.0 B
tt6385540
13 
tt10767748
10 
tt13598988
tt13539710
 
2
tt1714810
 
2
Other values (23)
23 

Length

Max length10
Median length9.5
Mean length9.5
Min length9

Characters and Unicode

Total characters551
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)39.7%

Sample

1st rowtt12923874
2nd rowtt11492320
3rd rowtt10727044
4th rowtt0401747
5th rowtt1714810

Common Values

ValueCountFrequency (%)
tt638554013
 
11.9%
tt1076774810
 
9.2%
tt135989888
 
7.3%
tt135397102
 
1.8%
tt17148102
 
1.8%
tt04017471
 
0.9%
tt124579461
 
0.9%
tt01851031
 
0.9%
tt04495451
 
0.9%
tt112191641
 
0.9%
Other values (18)18
 
16.5%
(Missing)51
46.8%

Length

2022-09-04T23:39:40.940716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt638554013
22.4%
tt1076774810
17.2%
tt135989888
13.8%
tt135397102
 
3.4%
tt17148102
 
3.4%
tt92067881
 
1.7%
tt107270441
 
1.7%
tt03375341
 
1.7%
tt40870321
 
1.7%
tt37676661
 
1.7%
Other values (18)18
31.0%

Most occurring characters

ValueCountFrequency (%)
t116
21.1%
867
12.2%
151
9.3%
750
9.1%
546
 
8.3%
446
 
8.3%
044
 
8.0%
342
 
7.6%
640
 
7.3%
930
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number435
78.9%
Lowercase Letter116
 
21.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
867
15.4%
151
11.7%
750
11.5%
546
10.6%
446
10.6%
044
10.1%
342
9.7%
640
9.2%
930
6.9%
219
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
t116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common435
78.9%
Latin116
 
21.1%

Most frequent character per script

Common
ValueCountFrequency (%)
867
15.4%
151
11.7%
750
11.5%
546
10.6%
446
10.6%
044
10.1%
342
9.7%
640
9.2%
930
6.9%
219
 
4.4%
Latin
ValueCountFrequency (%)
t116
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t116
21.1%
867
12.2%
151
9.3%
750
9.1%
546
 
8.3%
446
 
8.3%
044
 
8.0%
342
 
7.6%
640
 
7.3%
930
 
5.4%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)56.2%
Missing13
Missing (%)11.9%
Memory size1000.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/275/688063.jpg
13 
https://static.tvmaze.com/uploads/images/medium_portrait/284/710852.jpg
10 
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/289/723058.jpg
 
5
https://static.tvmaze.com/uploads/images/medium_portrait/392/980680.jpg
 
5
Other values (49)
55 

Length

Max length72
Median length71
Mean length70.9375
Min length69

Characters and Unicode

Total characters6810
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)44.8%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/394/985825.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/276/690795.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/304/762299.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/275/688063.jpg13
 
11.9%
https://static.tvmaze.com/uploads/images/medium_portrait/284/710852.jpg10
 
9.2%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg8
 
7.3%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723058.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/medium_portrait/392/980680.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
1.8%
Other values (44)45
41.3%
(Missing)13
 
11.9%

Length

2022-09-04T23:39:41.010645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/275/688063.jpg13
 
13.5%
https://static.tvmaze.com/uploads/images/medium_portrait/284/710852.jpg10
 
10.4%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg8
 
8.3%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723058.jpg5
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/392/980680.jpg5
 
5.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.1%
Other values (44)45
46.9%

Most occurring characters

ValueCountFrequency (%)
/672
 
9.9%
t672
 
9.9%
a480
 
7.0%
m480
 
7.0%
p384
 
5.6%
s384
 
5.6%
i384
 
5.6%
.288
 
4.2%
e288
 
4.2%
o288
 
4.2%
Other values (22)2490
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4800
70.5%
Other Punctuation1056
 
15.5%
Decimal Number858
 
12.6%
Connector Punctuation96
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t672
14.0%
a480
10.0%
m480
10.0%
p384
 
8.0%
s384
 
8.0%
i384
 
8.0%
e288
 
6.0%
o288
 
6.0%
d192
 
4.0%
u192
 
4.0%
Other values (8)1056
22.0%
Decimal Number
ValueCountFrequency (%)
8141
16.4%
2124
14.5%
790
10.5%
084
9.8%
583
9.7%
376
8.9%
172
8.4%
667
7.8%
963
7.3%
458
6.8%
Other Punctuation
ValueCountFrequency (%)
/672
63.6%
.288
27.3%
:96
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4800
70.5%
Common2010
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t672
14.0%
a480
10.0%
m480
10.0%
p384
 
8.0%
s384
 
8.0%
i384
 
8.0%
e288
 
6.0%
o288
 
6.0%
d192
 
4.0%
u192
 
4.0%
Other values (8)1056
22.0%
Common
ValueCountFrequency (%)
/672
33.4%
.288
14.3%
8141
 
7.0%
2124
 
6.2%
_96
 
4.8%
:96
 
4.8%
790
 
4.5%
084
 
4.2%
583
 
4.1%
376
 
3.8%
Other values (4)260
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII6810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/672
 
9.9%
t672
 
9.9%
a480
 
7.0%
m480
 
7.0%
p384
 
5.6%
s384
 
5.6%
i384
 
5.6%
.288
 
4.2%
e288
 
4.2%
o288
 
4.2%
Other values (22)2490
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct54
Distinct (%)56.2%
Missing13
Missing (%)11.9%
Memory size1000.0 B
https://static.tvmaze.com/uploads/images/original_untouched/275/688063.jpg
13 
https://static.tvmaze.com/uploads/images/original_untouched/284/710852.jpg
10 
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg
https://static.tvmaze.com/uploads/images/original_untouched/289/723058.jpg
 
5
https://static.tvmaze.com/uploads/images/original_untouched/392/980680.jpg
 
5
Other values (49)
55 

Length

Max length75
Median length74
Mean length73.9375
Min length72

Characters and Unicode

Total characters7098
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)44.8%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/394/985825.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/276/690795.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/304/762299.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/275/688063.jpg13
 
11.9%
https://static.tvmaze.com/uploads/images/original_untouched/284/710852.jpg10
 
9.2%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg8
 
7.3%
https://static.tvmaze.com/uploads/images/original_untouched/289/723058.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/original_untouched/392/980680.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
1.8%
Other values (44)45
41.3%
(Missing)13
 
11.9%

Length

2022-09-04T23:39:41.090646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/275/688063.jpg13
 
13.5%
https://static.tvmaze.com/uploads/images/original_untouched/284/710852.jpg10
 
10.4%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg8
 
8.3%
https://static.tvmaze.com/uploads/images/original_untouched/289/723058.jpg5
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/392/980680.jpg5
 
5.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.1%
Other values (44)45
46.9%

Most occurring characters

ValueCountFrequency (%)
/672
 
9.5%
t576
 
8.1%
a480
 
6.8%
s384
 
5.4%
i384
 
5.4%
o384
 
5.4%
p288
 
4.1%
c288
 
4.1%
.288
 
4.1%
g288
 
4.1%
Other values (23)3066
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5088
71.7%
Other Punctuation1056
 
14.9%
Decimal Number858
 
12.1%
Connector Punctuation96
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t576
 
11.3%
a480
 
9.4%
s384
 
7.5%
i384
 
7.5%
o384
 
7.5%
p288
 
5.7%
c288
 
5.7%
g288
 
5.7%
m288
 
5.7%
e288
 
5.7%
Other values (9)1440
28.3%
Decimal Number
ValueCountFrequency (%)
8141
16.4%
2124
14.5%
790
10.5%
084
9.8%
583
9.7%
376
8.9%
172
8.4%
667
7.8%
963
7.3%
458
6.8%
Other Punctuation
ValueCountFrequency (%)
/672
63.6%
.288
27.3%
:96
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5088
71.7%
Common2010
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t576
 
11.3%
a480
 
9.4%
s384
 
7.5%
i384
 
7.5%
o384
 
7.5%
p288
 
5.7%
c288
 
5.7%
g288
 
5.7%
m288
 
5.7%
e288
 
5.7%
Other values (9)1440
28.3%
Common
ValueCountFrequency (%)
/672
33.4%
.288
14.3%
8141
 
7.0%
2124
 
6.2%
:96
 
4.8%
_96
 
4.8%
790
 
4.5%
084
 
4.2%
583
 
4.1%
376
 
3.8%
Other values (4)260
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/672
 
9.5%
t576
 
8.1%
a480
 
6.8%
s384
 
5.4%
i384
 
5.4%
o384
 
5.4%
p288
 
4.1%
c288
 
4.1%
.288
 
4.1%
g288
 
4.1%
Other values (23)3066
43.2%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING

Distinct50
Distinct (%)57.5%
Missing22
Missing (%)20.2%
Memory size1000.0 B
<p><b>Hilda</b> follows the adventures of a fearless blue-haired girl as she travels from her home in a vast magical wilderness full of elves and giants, to the bustling city of Trolberg, where she meets new friends and mysterious creatures who are stranger - and more dangerous - than she ever expected.</p>
13 
<p><b>Tiny Pretty Things</b> is set in the world of an elite ballet academy and charts the rise and fall of young adults who live far from their homes, each standing on the verge of greatness or ruin. As Chicago's only elite dance school, the Archer School of Ballet serves as the company school for the city's renowned professional company: City Works Ballet. The Archer School is an oasis for an array of dancers: rich and poor, from north and south, and a range of backgrounds. Yet they all share a rare talent and passion for dance, a loyal sense of community... and when it comes to their dreams, no Plan B.</p>
10 
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>
<p>A documentary series about Tofaş owners and culture from 7 regions of Turkey.</p>
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>
 
2
Other values (45)
49 

Length

Max length913
Median length623
Mean length355.7586207
Min length58

Characters and Unicode

Total characters30951
Distinct characters134
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)47.1%

Sample

1st row<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>
2nd row<p>One day in 20XX, the alien pig prince who planned to take a human body as his home arrived on Earth, but unexpectedly discovered that the human being he wanted to live in had not yet been born! The pig prince, who has nowhere to settle down, got to know Saiji and Rubi. The three pulled various funny pranks on humans, causing humans to have baldness, bad breath, headaches, emotional crisis and other problems.</p>
3rd row<p>The master of Ye Xing Yun will ascend to heaven, leaving behind the great strength of the Tian Yuan Sect, and Ye Xing Yun making the new Sovereign of the Tian Yuan Sect, and at the request of his master, seek revenge by entering into a small family while waiting to perform revenge. Ye Xing Yun embarks on an extremely dangerous road, but with his strategy, and with the help of the masters of the Tian Yuan Sect, his long-term strategy of confrontation with the huge Zhou dynasty.</p>
4th row<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
5th row<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p><b>Hilda</b> follows the adventures of a fearless blue-haired girl as she travels from her home in a vast magical wilderness full of elves and giants, to the bustling city of Trolberg, where she meets new friends and mysterious creatures who are stranger - and more dangerous - than she ever expected.</p>13
 
11.9%
<p><b>Tiny Pretty Things</b> is set in the world of an elite ballet academy and charts the rise and fall of young adults who live far from their homes, each standing on the verge of greatness or ruin. As Chicago's only elite dance school, the Archer School of Ballet serves as the company school for the city's renowned professional company: City Works Ballet. The Archer School is an oasis for an array of dancers: rich and poor, from north and south, and a range of backgrounds. Yet they all share a rare talent and passion for dance, a loyal sense of community... and when it comes to their dreams, no Plan B.</p>10
 
9.2%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>8
 
7.3%
<p>A documentary series about Tofaş owners and culture from 7 regions of Turkey.</p>5
 
4.6%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
1.8%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
1.8%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
1.8%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
1.8%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
1.8%
<p>Feelgood bromance where Alex Rosen and Aune Sand (<b>Alex and Aune</b>) get to know each other better. With each other, and the inhabitants of the village Bleik in Vesterålen where they will live together for five weeks towards St. Hans.</p>1
 
0.9%
Other values (40)40
36.7%
(Missing)22
20.2%

Length

2022-09-04T23:39:41.186647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the273
 
5.2%
and223
 
4.2%
of200
 
3.8%
to141
 
2.7%
a140
 
2.6%
in92
 
1.7%
their62
 
1.2%
from60
 
1.1%
as54
 
1.0%
for54
 
1.0%
Other values (1357)3991
75.4%

Most occurring characters

ValueCountFrequency (%)
5191
16.8%
e2833
 
9.2%
a1963
 
6.3%
o1839
 
5.9%
t1826
 
5.9%
n1671
 
5.4%
s1618
 
5.2%
r1616
 
5.2%
i1373
 
4.4%
h1236
 
4.0%
Other values (124)9785
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter23347
75.4%
Space Separator5203
 
16.8%
Uppercase Letter853
 
2.8%
Other Punctuation846
 
2.7%
Math Symbol554
 
1.8%
Dash Punctuation70
 
0.2%
Decimal Number52
 
0.2%
Other Letter13
 
< 0.1%
Close Punctuation6
 
< 0.1%
Open Punctuation6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2833
12.1%
a1963
 
8.4%
o1839
 
7.9%
t1826
 
7.8%
n1671
 
7.2%
s1618
 
6.9%
r1616
 
6.9%
i1373
 
5.9%
h1236
 
5.3%
l1001
 
4.3%
Other values (53)6371
27.3%
Uppercase Letter
ValueCountFrequency (%)
T108
 
12.7%
A79
 
9.3%
S67
 
7.9%
Y62
 
7.3%
B56
 
6.6%
W55
 
6.4%
M41
 
4.8%
P35
 
4.1%
L32
 
3.8%
C31
 
3.6%
Other values (20)287
33.6%
Other Letter
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%
Other Punctuation
ValueCountFrequency (%)
,286
33.8%
.257
30.4%
/140
16.5%
'76
 
9.0%
"40
 
4.7%
:29
 
3.4%
!10
 
1.2%
?6
 
0.7%
&1
 
0.1%
;1
 
0.1%
Decimal Number
ValueCountFrequency (%)
013
25.0%
211
21.2%
77
13.5%
16
11.5%
95
 
9.6%
35
 
9.6%
53
 
5.8%
81
 
1.9%
61
 
1.9%
Space Separator
ValueCountFrequency (%)
5191
99.8%
 12
 
0.2%
Math Symbol
ValueCountFrequency (%)
<277
50.0%
>277
50.0%
Dash Punctuation
ValueCountFrequency (%)
-62
88.6%
8
 
11.4%
Close Punctuation
ValueCountFrequency (%)
)6
100.0%
Open Punctuation
ValueCountFrequency (%)
(6
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin23812
76.9%
Common6738
 
21.8%
Cyrillic388
 
1.3%
Han13
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2833
11.9%
a1963
 
8.2%
o1839
 
7.7%
t1826
 
7.7%
n1671
 
7.0%
s1618
 
6.8%
r1616
 
6.8%
i1373
 
5.8%
h1236
 
5.2%
l1001
 
4.2%
Other values (49)6836
28.7%
Cyrillic
ValueCountFrequency (%)
и38
 
9.8%
е38
 
9.8%
т37
 
9.5%
о35
 
9.0%
с25
 
6.4%
н24
 
6.2%
а24
 
6.2%
м21
 
5.4%
в16
 
4.1%
р15
 
3.9%
Other values (24)115
29.6%
Common
ValueCountFrequency (%)
5191
77.0%
,286
 
4.2%
<277
 
4.1%
>277
 
4.1%
.257
 
3.8%
/140
 
2.1%
'76
 
1.1%
-62
 
0.9%
"40
 
0.6%
:29
 
0.4%
Other values (18)103
 
1.5%
Han
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII30517
98.6%
Cyrillic388
 
1.3%
None25
 
0.1%
CJK13
 
< 0.1%
Punctuation8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5191
17.0%
e2833
 
9.3%
a1963
 
6.4%
o1839
 
6.0%
t1826
 
6.0%
n1671
 
5.5%
s1618
 
5.3%
r1616
 
5.3%
i1373
 
4.5%
h1236
 
4.1%
Other values (68)9351
30.6%
Cyrillic
ValueCountFrequency (%)
и38
 
9.8%
е38
 
9.8%
т37
 
9.5%
о35
 
9.0%
с25
 
6.4%
н24
 
6.2%
а24
 
6.2%
м21
 
5.4%
в16
 
4.1%
р15
 
3.9%
Other values (24)115
29.6%
None
ValueCountFrequency (%)
 12
48.0%
ş5
20.0%
é3
 
12.0%
ā1
 
4.0%
å1
 
4.0%
ç1
 
4.0%
ı1
 
4.0%
è1
 
4.0%
Punctuation
ValueCountFrequency (%)
8
100.0%
CJK
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct61
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1638623495
Minimum1602172227
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:41.283917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1602172227
5-th percentile1611477684
Q11618466682
median1643057695
Q31654107441
95-th percentile1661131000
Maximum1662346277
Range60174050
Interquartile range (IQR)35640759

Descriptive statistics

Standard deviation18351728.23
Coefficient of variation (CV)0.01119947828
Kurtosis-1.28397357
Mean1638623495
Median Absolute Deviation (MAD)14942577
Skewness-0.4194085128
Sum1.78609961 × 1011
Variance3.367859292 × 1014
MonotonicityNot monotonic
2022-09-04T23:39:41.380917image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165800027213
 
11.9%
163766347310
 
9.2%
16124781458
 
7.3%
16115389485
 
4.6%
16151929545
 
4.6%
16430576955
 
4.6%
16196365813
 
2.8%
16481900582
 
1.8%
16090607262
 
1.8%
16508264802
 
1.8%
Other values (51)54
49.5%
ValueCountFrequency (%)
16021722271
 
0.9%
16090607262
 
1.8%
16095351412
 
1.8%
16114368421
 
0.9%
16115389485
4.6%
16124781458
7.3%
16130883481
 
0.9%
16133564461
 
0.9%
16151929545
4.6%
16164229131
 
0.9%
ValueCountFrequency (%)
16623462771
0.9%
16621306411
0.9%
16620480541
0.9%
16616322671
0.9%
16613636441
0.9%
16612693571
0.9%
16609234641
0.9%
16609157101
0.9%
16607584791
0.9%
16602678031
0.9%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct61
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://api.tvmaze.com/shows/25910
13 
https://api.tvmaze.com/shows/43293
10 
https://api.tvmaze.com/shows/52524
https://api.tvmaze.com/shows/52479
 
5
https://api.tvmaze.com/shows/51954
 
5
Other values (56)
68 

Length

Max length34
Median length34
Mean length33.95412844
Min length32

Characters and Unicode

Total characters3701
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)44.0%

Sample

1st rowhttps://api.tvmaze.com/shows/52181
2nd rowhttps://api.tvmaze.com/shows/52181
3rd rowhttps://api.tvmaze.com/shows/56655
4th rowhttps://api.tvmaze.com/shows/50916
5th rowhttps://api.tvmaze.com/shows/54610

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/2591013
 
11.9%
https://api.tvmaze.com/shows/4329310
 
9.2%
https://api.tvmaze.com/shows/525248
 
7.3%
https://api.tvmaze.com/shows/524795
 
4.6%
https://api.tvmaze.com/shows/519545
 
4.6%
https://api.tvmaze.com/shows/601565
 
4.6%
https://api.tvmaze.com/shows/549963
 
2.8%
https://api.tvmaze.com/shows/152502
 
1.8%
https://api.tvmaze.com/shows/521592
 
1.8%
https://api.tvmaze.com/shows/521082
 
1.8%
Other values (51)54
49.5%

Length

2022-09-04T23:39:41.476984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/2591013
 
11.9%
https://api.tvmaze.com/shows/4329310
 
9.2%
https://api.tvmaze.com/shows/525248
 
7.3%
https://api.tvmaze.com/shows/524795
 
4.6%
https://api.tvmaze.com/shows/519545
 
4.6%
https://api.tvmaze.com/shows/601565
 
4.6%
https://api.tvmaze.com/shows/549963
 
2.8%
https://api.tvmaze.com/shows/521042
 
1.8%
https://api.tvmaze.com/shows/547622
 
1.8%
https://api.tvmaze.com/shows/521812
 
1.8%
Other values (51)54
49.5%

Most occurring characters

ValueCountFrequency (%)
/436
 
11.8%
s327
 
8.8%
t327
 
8.8%
h218
 
5.9%
p218
 
5.9%
a218
 
5.9%
o218
 
5.9%
.218
 
5.9%
m218
 
5.9%
e109
 
2.9%
Other values (16)1194
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2398
64.8%
Other Punctuation763
 
20.6%
Decimal Number540
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s327
13.6%
t327
13.6%
h218
9.1%
p218
9.1%
a218
9.1%
o218
9.1%
m218
9.1%
e109
 
4.5%
w109
 
4.5%
c109
 
4.5%
Other values (3)327
13.6%
Decimal Number
ValueCountFrequency (%)
5107
19.8%
278
14.4%
466
12.2%
159
10.9%
955
10.2%
047
8.7%
641
 
7.6%
338
 
7.0%
725
 
4.6%
824
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/436
57.1%
.218
28.6%
:109
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2398
64.8%
Common1303
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/436
33.5%
.218
16.7%
:109
 
8.4%
5107
 
8.2%
278
 
6.0%
466
 
5.1%
159
 
4.5%
955
 
4.2%
047
 
3.6%
641
 
3.1%
Other values (3)87
 
6.7%
Latin
ValueCountFrequency (%)
s327
13.6%
t327
13.6%
h218
9.1%
p218
9.1%
a218
9.1%
o218
9.1%
m218
9.1%
e109
 
4.5%
w109
 
4.5%
c109
 
4.5%
Other values (3)327
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3701
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/436
 
11.8%
s327
 
8.8%
t327
 
8.8%
h218
 
5.9%
p218
 
5.9%
a218
 
5.9%
o218
 
5.9%
.218
 
5.9%
m218
 
5.9%
e109
 
2.9%
Other values (16)1194
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct61
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
https://api.tvmaze.com/episodes/2221911
13 
https://api.tvmaze.com/episodes/1977840
10 
https://api.tvmaze.com/episodes/1988079
https://api.tvmaze.com/episodes/1987350
 
5
https://api.tvmaze.com/episodes/1971211
 
5
Other values (56)
68 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4251
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)44.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1982412
2nd rowhttps://api.tvmaze.com/episodes/1982412
3rd rowhttps://api.tvmaze.com/episodes/2383576
4th rowhttps://api.tvmaze.com/episodes/1945592
5th rowhttps://api.tvmaze.com/episodes/2381296

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/222191113
 
11.9%
https://api.tvmaze.com/episodes/197784010
 
9.2%
https://api.tvmaze.com/episodes/19880798
 
7.3%
https://api.tvmaze.com/episodes/19873505
 
4.6%
https://api.tvmaze.com/episodes/19712115
 
4.6%
https://api.tvmaze.com/episodes/22649425
 
4.6%
https://api.tvmaze.com/episodes/20790093
 
2.8%
https://api.tvmaze.com/episodes/23012762
 
1.8%
https://api.tvmaze.com/episodes/19776512
 
1.8%
https://api.tvmaze.com/episodes/19762022
 
1.8%
Other values (51)54
49.5%

Length

2022-09-04T23:39:41.667449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/222191113
 
11.9%
https://api.tvmaze.com/episodes/197784010
 
9.2%
https://api.tvmaze.com/episodes/19880798
 
7.3%
https://api.tvmaze.com/episodes/19873505
 
4.6%
https://api.tvmaze.com/episodes/19712115
 
4.6%
https://api.tvmaze.com/episodes/22649425
 
4.6%
https://api.tvmaze.com/episodes/20790093
 
2.8%
https://api.tvmaze.com/episodes/19760542
 
1.8%
https://api.tvmaze.com/episodes/20714942
 
1.8%
https://api.tvmaze.com/episodes/19824122
 
1.8%
Other values (51)54
49.5%

Most occurring characters

ValueCountFrequency (%)
/436
 
10.3%
p327
 
7.7%
s327
 
7.7%
e327
 
7.7%
t327
 
7.7%
o218
 
5.1%
a218
 
5.1%
i218
 
5.1%
.218
 
5.1%
m218
 
5.1%
Other values (16)1417
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2725
64.1%
Other Punctuation763
 
17.9%
Decimal Number763
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p327
12.0%
s327
12.0%
e327
12.0%
t327
12.0%
o218
8.0%
a218
8.0%
i218
8.0%
m218
8.0%
h109
 
4.0%
d109
 
4.0%
Other values (3)327
12.0%
Decimal Number
ValueCountFrequency (%)
2156
20.4%
1133
17.4%
999
13.0%
782
10.7%
073
9.6%
857
 
7.5%
352
 
6.8%
450
 
6.6%
532
 
4.2%
629
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/436
57.1%
.218
28.6%
:109
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2725
64.1%
Common1526
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/436
28.6%
.218
14.3%
2156
 
10.2%
1133
 
8.7%
:109
 
7.1%
999
 
6.5%
782
 
5.4%
073
 
4.8%
857
 
3.7%
352
 
3.4%
Other values (3)111
 
7.3%
Latin
ValueCountFrequency (%)
p327
12.0%
s327
12.0%
e327
12.0%
t327
12.0%
o218
8.0%
a218
8.0%
i218
8.0%
m218
8.0%
h109
 
4.0%
d109
 
4.0%
Other values (3)327
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/436
 
10.3%
p327
 
7.7%
s327
 
7.7%
e327
 
7.7%
t327
 
7.7%
o218
 
5.1%
a218
 
5.1%
i218
 
5.1%
.218
 
5.1%
m218
 
5.1%
Other values (16)1417
33.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct7
Distinct (%)100.0%
Missing102
Missing (%)93.6%
Memory size1000.0 B
https://api.tvmaze.com/episodes/2383577
https://api.tvmaze.com/episodes/2381297
https://api.tvmaze.com/episodes/2375174
https://api.tvmaze.com/episodes/2330184
https://api.tvmaze.com/episodes/2350915
Other values (2)

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters273
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2383577
2nd rowhttps://api.tvmaze.com/episodes/2381297
3rd rowhttps://api.tvmaze.com/episodes/2375174
4th rowhttps://api.tvmaze.com/episodes/2330184
5th rowhttps://api.tvmaze.com/episodes/2350915

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23835771
 
0.9%
https://api.tvmaze.com/episodes/23812971
 
0.9%
https://api.tvmaze.com/episodes/23751741
 
0.9%
https://api.tvmaze.com/episodes/23301841
 
0.9%
https://api.tvmaze.com/episodes/23509151
 
0.9%
https://api.tvmaze.com/episodes/23797021
 
0.9%
https://api.tvmaze.com/episodes/23488421
 
0.9%
(Missing)102
93.6%

Length

2022-09-04T23:39:41.735628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:41.810629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23835771
14.3%
https://api.tvmaze.com/episodes/23812971
14.3%
https://api.tvmaze.com/episodes/23751741
14.3%
https://api.tvmaze.com/episodes/23301841
14.3%
https://api.tvmaze.com/episodes/23509151
14.3%
https://api.tvmaze.com/episodes/23797021
14.3%
https://api.tvmaze.com/episodes/23488421
14.3%

Most occurring characters

ValueCountFrequency (%)
/28
 
10.3%
e21
 
7.7%
p21
 
7.7%
s21
 
7.7%
t21
 
7.7%
o14
 
5.1%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
Other values (15)91
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter175
64.1%
Other Punctuation49
 
17.9%
Decimal Number49
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e21
12.0%
p21
12.0%
s21
12.0%
t21
12.0%
o14
8.0%
a14
8.0%
i14
8.0%
m14
8.0%
d7
 
4.0%
h7
 
4.0%
Other values (3)21
12.0%
Decimal Number
ValueCountFrequency (%)
210
20.4%
39
18.4%
77
14.3%
85
10.2%
54
 
8.2%
14
 
8.2%
44
 
8.2%
93
 
6.1%
03
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/28
57.1%
.14
28.6%
:7
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin175
64.1%
Common98
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e21
12.0%
p21
12.0%
s21
12.0%
t21
12.0%
o14
8.0%
a14
8.0%
i14
8.0%
m14
8.0%
d7
 
4.0%
h7
 
4.0%
Other values (3)21
12.0%
Common
ValueCountFrequency (%)
/28
28.6%
.14
14.3%
210
 
10.2%
39
 
9.2%
77
 
7.1%
:7
 
7.1%
85
 
5.1%
54
 
4.1%
14
 
4.1%
44
 
4.1%
Other values (2)6
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/28
 
10.3%
e21
 
7.7%
p21
 
7.7%
s21
 
7.7%
t21
 
7.7%
o14
 
5.1%
a14
 
5.1%
i14
 
5.1%
.14
 
5.1%
m14
 
5.1%
Other values (15)91
33.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct34
Distinct (%)100.0%
Missing75
Missing (%)68.8%
Memory size1000.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/288/722218.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/722212.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/722213.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/722214.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/722215.jpg
 
1
Other values (29)
29 

Length

Max length73
Median length72
Mean length72.02941176
Min length72

Characters and Unicode

Total characters2449
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726348.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721853.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/319/799925.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/722184.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/722185.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/288/722218.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722212.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722213.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722214.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722215.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722216.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722217.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722219.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722210.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722356.jpg1
 
0.9%
Other values (24)24
 
22.0%
(Missing)75
68.8%

Length

2022-09-04T23:39:41.901627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/288/722218.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722189.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721853.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/319/799925.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722184.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722185.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722186.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722187.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722196.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/medium_landscape/288/722212.jpg1
 
2.9%
Other values (24)24
70.6%

Most occurring characters

ValueCountFrequency (%)
/238
 
9.7%
a204
 
8.3%
s170
 
6.9%
m170
 
6.9%
t170
 
6.9%
p136
 
5.6%
e136
 
5.6%
2108
 
4.4%
i102
 
4.2%
c102
 
4.2%
Other values (22)913
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1734
70.8%
Other Punctuation374
 
15.3%
Decimal Number307
 
12.5%
Connector Punctuation34
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a204
11.8%
s170
9.8%
m170
9.8%
t170
9.8%
p136
 
7.8%
e136
 
7.8%
i102
 
5.9%
c102
 
5.9%
d102
 
5.9%
u68
 
3.9%
Other values (8)374
21.6%
Decimal Number
ValueCountFrequency (%)
2108
35.2%
872
23.5%
741
 
13.4%
130
 
9.8%
914
 
4.6%
310
 
3.3%
49
 
2.9%
59
 
2.9%
08
 
2.6%
66
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/238
63.6%
.102
27.3%
:34
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1734
70.8%
Common715
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a204
11.8%
s170
9.8%
m170
9.8%
t170
9.8%
p136
 
7.8%
e136
 
7.8%
i102
 
5.9%
c102
 
5.9%
d102
 
5.9%
u68
 
3.9%
Other values (8)374
21.6%
Common
ValueCountFrequency (%)
/238
33.3%
2108
15.1%
.102
14.3%
872
 
10.1%
741
 
5.7%
_34
 
4.8%
:34
 
4.8%
130
 
4.2%
914
 
2.0%
310
 
1.4%
Other values (4)32
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2449
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/238
 
9.7%
a204
 
8.3%
s170
 
6.9%
m170
 
6.9%
t170
 
6.9%
p136
 
5.6%
e136
 
5.6%
2108
 
4.4%
i102
 
4.2%
c102
 
4.2%
Other values (22)913
37.3%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct34
Distinct (%)100.0%
Missing75
Missing (%)68.8%
Memory size1000.0 B
https://static.tvmaze.com/uploads/images/original_untouched/288/722218.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/722212.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/722213.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/722214.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/722215.jpg
 
1
Other values (29)
29 

Length

Max length75
Median length74
Mean length74.02941176
Min length74

Characters and Unicode

Total characters2517
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726348.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721853.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/319/799925.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/722184.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/722185.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/288/722218.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722212.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722213.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722214.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722215.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722216.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722217.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722219.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722210.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722356.jpg1
 
0.9%
Other values (24)24
 
22.0%
(Missing)75
68.8%

Length

2022-09-04T23:39:41.974068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/288/722218.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722189.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/721853.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/319/799925.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722184.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722185.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722186.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722187.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722196.jpg1
 
2.9%
https://static.tvmaze.com/uploads/images/original_untouched/288/722212.jpg1
 
2.9%
Other values (24)24
70.6%

Most occurring characters

ValueCountFrequency (%)
/238
 
9.5%
t204
 
8.1%
a170
 
6.8%
s136
 
5.4%
o136
 
5.4%
i136
 
5.4%
2108
 
4.3%
u102
 
4.1%
e102
 
4.1%
m102
 
4.1%
Other values (23)1083
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1802
71.6%
Other Punctuation374
 
14.9%
Decimal Number307
 
12.2%
Connector Punctuation34
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t204
 
11.3%
a170
 
9.4%
s136
 
7.5%
o136
 
7.5%
i136
 
7.5%
u102
 
5.7%
e102
 
5.7%
m102
 
5.7%
c102
 
5.7%
g102
 
5.7%
Other values (9)510
28.3%
Decimal Number
ValueCountFrequency (%)
2108
35.2%
872
23.5%
741
 
13.4%
130
 
9.8%
914
 
4.6%
310
 
3.3%
49
 
2.9%
59
 
2.9%
08
 
2.6%
66
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/238
63.6%
.102
27.3%
:34
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1802
71.6%
Common715
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t204
 
11.3%
a170
 
9.4%
s136
 
7.5%
o136
 
7.5%
i136
 
7.5%
u102
 
5.7%
e102
 
5.7%
m102
 
5.7%
c102
 
5.7%
g102
 
5.7%
Other values (9)510
28.3%
Common
ValueCountFrequency (%)
/238
33.3%
2108
15.1%
.102
14.3%
872
 
10.1%
741
 
5.7%
_34
 
4.8%
:34
 
4.8%
130
 
4.2%
914
 
2.0%
310
 
1.4%
Other values (4)32
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/238
 
9.5%
t204
 
8.1%
a170
 
6.8%
s136
 
5.4%
o136
 
5.4%
i136
 
5.4%
2108
 
4.3%
u102
 
4.1%
e102
 
4.1%
m102
 
4.1%
Other values (23)1083
43.0%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)100.0%
Missing103
Missing (%)94.5%
Infinite0
Infinite (%)0.0%
Mean390.5
Minimum30
Maximum755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1000.0 B
2022-09-04T23:39:42.039066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50.5
Q1177.5
median444
Q3547
95-th percentile705.75
Maximum755
Range725
Interquartile range (IQR)369.5

Descriptive statistics

Standard deviation277.1149581
Coefficient of variation (CV)0.709641378
Kurtosis-1.314693001
Mean390.5
Median Absolute Deviation (MAD)212.5
Skewness-0.1895491999
Sum2343
Variance76792.7
MonotonicityNot monotonic
2022-09-04T23:39:42.105751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5141
 
0.9%
3741
 
0.9%
7551
 
0.9%
1121
 
0.9%
5581
 
0.9%
301
 
0.9%
(Missing)103
94.5%
ValueCountFrequency (%)
301
0.9%
1121
0.9%
3741
0.9%
5141
0.9%
5581
0.9%
7551
0.9%
ValueCountFrequency (%)
7551
0.9%
5581
0.9%
5141
0.9%
3741
0.9%
1121
0.9%
301
0.9%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing103
Missing (%)94.5%
Memory size1000.0 B
ТВ-3
TV Globo
Show TV
RTL4
TV3

Length

Max length11
Median length7.5
Mean length6.166666667
Min length3

Characters and Unicode

Total characters37
Distinct characters24
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowТВ-3
2nd rowTV Globo
3rd rowShow TV
4th rowRTL4
5th rowTV3

Common Values

ValueCountFrequency (%)
ТВ-31
 
0.9%
TV Globo1
 
0.9%
Show TV1
 
0.9%
RTL41
 
0.9%
TV31
 
0.9%
USA Network1
 
0.9%
(Missing)103
94.5%

Length

2022-09-04T23:39:42.201817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:42.292507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
tv2
22.2%
тв-31
11.1%
globo1
11.1%
show1
11.1%
rtl41
11.1%
tv31
11.1%
usa1
11.1%
network1
11.1%

Most occurring characters

ValueCountFrequency (%)
T4
 
10.8%
o4
 
10.8%
V3
 
8.1%
3
 
8.1%
32
 
5.4%
S2
 
5.4%
w2
 
5.4%
Т1
 
2.7%
41
 
2.7%
r1
 
2.7%
Other values (14)14
37.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter17
45.9%
Lowercase Letter13
35.1%
Space Separator3
 
8.1%
Decimal Number3
 
8.1%
Dash Punctuation1
 
2.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T4
23.5%
V3
17.6%
S2
11.8%
Т1
 
5.9%
N1
 
5.9%
A1
 
5.9%
U1
 
5.9%
L1
 
5.9%
R1
 
5.9%
В1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
o4
30.8%
w2
15.4%
r1
 
7.7%
t1
 
7.7%
e1
 
7.7%
h1
 
7.7%
b1
 
7.7%
l1
 
7.7%
k1
 
7.7%
Decimal Number
ValueCountFrequency (%)
32
66.7%
41
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin28
75.7%
Common7
 
18.9%
Cyrillic2
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T4
14.3%
o4
14.3%
V3
 
10.7%
S2
 
7.1%
w2
 
7.1%
r1
 
3.6%
t1
 
3.6%
e1
 
3.6%
N1
 
3.6%
A1
 
3.6%
Other values (8)8
28.6%
Common
ValueCountFrequency (%)
3
42.9%
32
28.6%
41
 
14.3%
-1
 
14.3%
Cyrillic
ValueCountFrequency (%)
Т1
50.0%
В1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII35
94.6%
Cyrillic2
 
5.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T4
 
11.4%
o4
 
11.4%
V3
 
8.6%
3
 
8.6%
32
 
5.7%
S2
 
5.7%
w2
 
5.7%
41
 
2.9%
r1
 
2.9%
t1
 
2.9%
Other values (12)12
34.3%
Cyrillic
ValueCountFrequency (%)
Т1
50.0%
В1
50.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing103
Missing (%)94.5%
Memory size1000.0 B
Russian Federation
Brazil
Turkey
Netherlands
Sweden

Length

Max length18
Median length15.5
Mean length10
Min length6

Characters and Unicode

Total characters60
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowRussian Federation
2nd rowBrazil
3rd rowTurkey
4th rowNetherlands
5th rowSweden

Common Values

ValueCountFrequency (%)
Russian Federation1
 
0.9%
Brazil1
 
0.9%
Turkey1
 
0.9%
Netherlands1
 
0.9%
Sweden1
 
0.9%
United States1
 
0.9%
(Missing)103
94.5%

Length

2022-09-04T23:39:42.377975image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:42.466627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
12.5%
federation1
12.5%
brazil1
12.5%
turkey1
12.5%
netherlands1
12.5%
sweden1
12.5%
united1
12.5%
states1
12.5%

Most occurring characters

ValueCountFrequency (%)
e9
15.0%
a5
 
8.3%
n5
 
8.3%
t5
 
8.3%
s4
 
6.7%
i4
 
6.7%
d4
 
6.7%
r4
 
6.7%
S2
 
3.3%
2
 
3.3%
Other values (14)16
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter50
83.3%
Uppercase Letter8
 
13.3%
Space Separator2
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e9
18.0%
a5
10.0%
n5
10.0%
t5
10.0%
s4
8.0%
i4
8.0%
d4
8.0%
r4
8.0%
l2
 
4.0%
u2
 
4.0%
Other values (6)6
12.0%
Uppercase Letter
ValueCountFrequency (%)
S2
25.0%
R1
12.5%
N1
12.5%
T1
12.5%
B1
12.5%
F1
12.5%
U1
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin58
96.7%
Common2
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e9
15.5%
a5
 
8.6%
n5
 
8.6%
t5
 
8.6%
s4
 
6.9%
i4
 
6.9%
d4
 
6.9%
r4
 
6.9%
S2
 
3.4%
l2
 
3.4%
Other values (13)14
24.1%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e9
15.0%
a5
 
8.3%
n5
 
8.3%
t5
 
8.3%
s4
 
6.7%
i4
 
6.7%
d4
 
6.7%
r4
 
6.7%
S2
 
3.3%
2
 
3.3%
Other values (14)16
26.7%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing103
Missing (%)94.5%
Memory size1000.0 B
RU
BR
TR
NL
SE

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters12
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowRU
2nd rowBR
3rd rowTR
4th rowNL
5th rowSE

Common Values

ValueCountFrequency (%)
RU1
 
0.9%
BR1
 
0.9%
TR1
 
0.9%
NL1
 
0.9%
SE1
 
0.9%
US1
 
0.9%
(Missing)103
94.5%

Length

2022-09-04T23:39:42.551496image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:42.628645image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
16.7%
br1
16.7%
tr1
16.7%
nl1
16.7%
se1
16.7%
us1
16.7%

Most occurring characters

ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter12
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R3
25.0%
U2
16.7%
S2
16.7%
B1
 
8.3%
T1
 
8.3%
N1
 
8.3%
L1
 
8.3%
E1
 
8.3%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing103
Missing (%)94.5%
Memory size1000.0 B
Asia/Kamchatka
America/Noronha
Europe/Istanbul
Europe/Amsterdam
Europe/Stockholm

Length

Max length16
Median length15.5
Mean length15.33333333
Min length14

Characters and Unicode

Total characters92
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka
2nd rowAmerica/Noronha
3rd rowEurope/Istanbul
4th rowEurope/Amsterdam
5th rowEurope/Stockholm

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
0.9%
America/Noronha1
 
0.9%
Europe/Istanbul1
 
0.9%
Europe/Amsterdam1
 
0.9%
Europe/Stockholm1
 
0.9%
America/New_York1
 
0.9%
(Missing)103
94.5%

Length

2022-09-04T23:39:42.709634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-04T23:39:42.795848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
16.7%
america/noronha1
16.7%
europe/istanbul1
16.7%
europe/amsterdam1
16.7%
europe/stockholm1
16.7%
america/new_york1
16.7%

Most occurring characters

ValueCountFrequency (%)
a9
 
9.8%
r8
 
8.7%
o8
 
8.7%
e7
 
7.6%
/6
 
6.5%
m6
 
6.5%
A4
 
4.3%
c4
 
4.3%
u4
 
4.3%
t4
 
4.3%
Other values (17)32
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter72
78.3%
Uppercase Letter13
 
14.1%
Other Punctuation6
 
6.5%
Connector Punctuation1
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a9
12.5%
r8
11.1%
o8
11.1%
e7
9.7%
m6
 
8.3%
c4
 
5.6%
u4
 
5.6%
t4
 
5.6%
p3
 
4.2%
s3
 
4.2%
Other values (8)16
22.2%
Uppercase Letter
ValueCountFrequency (%)
A4
30.8%
E3
23.1%
N2
15.4%
I1
 
7.7%
K1
 
7.7%
S1
 
7.7%
Y1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin85
92.4%
Common7
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a9
 
10.6%
r8
 
9.4%
o8
 
9.4%
e7
 
8.2%
m6
 
7.1%
A4
 
4.7%
c4
 
4.7%
u4
 
4.7%
t4
 
4.7%
p3
 
3.5%
Other values (15)28
32.9%
Common
ValueCountFrequency (%)
/6
85.7%
_1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a9
 
9.8%
r8
 
8.7%
o8
 
8.7%
e7
 
7.6%
/6
 
6.5%
m6
 
6.5%
A4
 
4.3%
c4
 
4.3%
u4
 
4.3%
t4
 
4.3%
Other values (17)32
34.8%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing109
Missing (%)100.0%
Memory size1000.0 B

Interactions

2022-09-04T23:39:33.096180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:22.671826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.639661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.522289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.553856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.476740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.505693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.394585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.350678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.164340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.147451image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.069516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.162227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:22.881820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.703661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.590286image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.636663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.543741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.576693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.455737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.408677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.233340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.227446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.138659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.224229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:22.966594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.777896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.670569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.718251image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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2022-09-04T23:39:27.656693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.525935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.476681image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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2022-09-04T23:39:31.305446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.220659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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2022-09-04T23:39:23.035178image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.852895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.877863image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.791412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.699485image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.724784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.598859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.540921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.385581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.380380image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.301698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.356538image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.104433image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.926173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.951065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.873092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.765416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.797184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.677859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.608074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.459662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.457379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.378698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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2022-09-04T23:39:23.170531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
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2022-09-04T23:39:25.948169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.961187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.868191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.750859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.675154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.530648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.534379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.457836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.498469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.238531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.072173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.100409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.023530image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.042408image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.940105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.820941image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.745156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.604263image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.612517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.535836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.569536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.305115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.148172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.182341image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.103679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.121490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.019105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.005522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.817158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.678256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.691517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.614836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.632772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.363115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.218358image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.252641image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.174656image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.191489image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.093105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.071876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.882303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.744262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.763517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.685836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.698761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.425255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.288426image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.324919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.246916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.272625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.168213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.136868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.949308image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.814259image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.838517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.760836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.769762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.500517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.368526image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.398919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.323421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.350275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.246213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.207015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.020682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.998257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.917516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.836382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:33.834693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:23.568516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:24.449291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:25.475861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:26.400492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:27.426278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:28.325583image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:29.277698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:30.097409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.074461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:31.994516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-09-04T23:39:32.915382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-09-04T23:39:42.897206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-04T23:39:43.158965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-04T23:39:43.417720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-04T23:39:43.706701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-04T23:39:34.121965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-04T23:39:35.186002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-04T23:39:35.724936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01982403https://www.tvmaze.com/episodes/1982403/volk-1x05-seria-05Серия 0515regular2020-12-142020-12-14T00:00:00+00:0048.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198240352181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian[Drama, Adventure, Mystery]Ended51.050.02020-12-072020-12-28https://premier.one/show/12339[Monday, Thursday]NaN23NaN281.0PremierRussian FederationRUAsia/KamchatkaNoneNoneNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/287/718741.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718741.jpgNone1640435531https://api.tvmaze.com/shows/52181https://api.tvmaze.com/episodes/1982412NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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22140387https://www.tvmaze.com/episodes/2140387/going-seventeen-2020-12-14-going-vs-seventeen-1GOING VS SEVENTEEN #1202042regular2020-12-142020-12-14T03:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/214038756655https://www.tvmaze.com/shows/56655/going-seventeenGoing SeventeenVarietyKorean[]Running30.030.02017-06-12NoneNone08:00[Wednesday]NaN69NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNoneNaN330462.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/985825.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/985825.jpg<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>1662048054https://api.tvmaze.com/shows/56655https://api.tvmaze.com/episodes/2383576https://api.tvmaze.com/episodes/2383577NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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42065442https://www.tvmaze.com/episodes/2065442/the-wonderland-of-ten-thousands-4x29-episode-29-157Episode 29 (157)429regular2020-12-142020-12-14T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/206544254610https://www.tvmaze.com/shows/54610/the-wonderland-of-ten-thousandsThe Wonderland of Ten ThousandsAnimationChinese[Anime, Fantasy, Romance]Running10.010.02018-03-30Nonehttps://v.qq.com/detail/5/5cuf8ahvxvm2587.html10:00[Monday, Thursday]NaN70NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN347112.0tt12923874https://static.tvmaze.com/uploads/images/medium_portrait/304/762299.jpghttps://static.tvmaze.com/uploads/images/original_untouched/304/762299.jpg<p>The master of Ye Xing Yun will ascend to heaven, leaving behind the great strength of the Tian Yuan Sect, and Ye Xing Yun making the new Sovereign of the Tian Yuan Sect, and at the request of his master, seek revenge by entering into a small family while waiting to perform revenge. Ye Xing Yun embarks on an extremely dangerous road, but with his strategy, and with the help of the masters of the Tian Yuan Sect, his long-term strategy of confrontation with the huge Zhou dynasty.</p>1661632267https://api.tvmaze.com/shows/54610https://api.tvmaze.com/episodes/2381296https://api.tvmaze.com/episodes/2381297NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52071477https://www.tvmaze.com/episodes/2071477/youths-in-the-breeze-1x07-the-boy-and-the-cat-07THE BOY AND THE CAT #0717regular2020-12-142020-12-14T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207147754762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62071478https://www.tvmaze.com/episodes/2071478/youths-in-the-breeze-1x08-the-boy-and-the-cat-08THE BOY AND THE CAT #0818regular2020-12-142020-12-14T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207147854762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72080225https://www.tvmaze.com/episodes/2080225/supreme-god-emperor-1x63-episode-63Episode 63163regular2020-12-142020-12-14T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208022555019https://www.tvmaze.com/shows/55019/supreme-god-emperorSupreme God EmperorAnimationChinese[Anime]Running10.010.02020-05-18Nonehttps://v.qq.com/detail/m/mzc00200ilydv1a.html10:00[Monday, Friday]NaN63NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN388383.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778540.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778540.jpg<p>Ten thousand years ago, Muyun's fairy King was secretly accounted for by holding a Zhuxian figure, and after a long sleep, he awakened in the famous "Muyun waste" of the southern Yun Empire in the Land of Heaven. When Muyun first woke up, he was deliberately bothered by the student Miaoxianyu. Muyun easily completed the Miaoxianyu trap, and he gave more and more alchemy skills by analogy, so the Alchemy masters outside the door could not ask for appreciation. Endless back home, Mu Yun learns that he is about to marry Nona Qin Qin Mengyao. Qin Mengyao was cold and toxic, but could not live until he was 20 years old. The marriage was only for the sake of pastoralists and family of Qin. However, under Mu Linchen's enticement, Mu Yun approves the family's issue on the condition of alchemy.</p><p><br /> </p>1653896222https://api.tvmaze.com/shows/55019https://api.tvmaze.com/episodes/2257583NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81977322https://www.tvmaze.com/episodes/1977322/stjernestov-1x14-episode-14Episode 14114regular2020-12-1406:002020-12-14T05:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197732250752https://www.tvmaze.com/shows/50752/stjernestovStjernestøvScriptedNorwegian[Drama, Children, Family]Ended20.020.02020-12-012020-12-24https://tv.nrk.no/serie/stjernestoev06:00[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN17NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN392649.0tt11492320https://static.tvmaze.com/uploads/images/medium_portrait/288/721951.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721951.jpg<p>The parents get divorced and Jo has to move to a new place. One day, Nordstjerna goes out, and Jo discovers that a girl with magical powers lives in the attic.</p>1611436842https://api.tvmaze.com/shows/50752https://api.tvmaze.com/episodes/1977332NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726348.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726348.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaN
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Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show._links.nextepisode.hrefimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel.country_embedded.show.image_embedded.show.webChannel
992005524https://www.tvmaze.com/episodes/2005524/this-week-in-tech-2020-12-14-i-cant-believe-its-not-minecraft-airpods-max-cyberpunk-2077-us-treasury-hack-halo-bandI Can't Believe It's Not Minecraft - AirPods Max, Cyberpunk 2077, US Treasury hack, Halo Band202050regular2020-12-142020-12-14T17:00:00+00:00120.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200552417584https://www.tvmaze.com/shows/17584/this-week-in-techThis Week in TechNewsEnglish[]Running120.0120.02005-04-17Nonehttps://twit.tv/shows/this-week-in-tech[Sunday]NaN24NaN102.0TwitUnited StatesUSAmerica/New_YorkNoneNoneNaN144991.0tt3541656https://static.tvmaze.com/uploads/images/medium_portrait/59/148015.jpghttps://static.tvmaze.com/uploads/images/original_untouched/59/148015.jpg<p>Your first podcast of the week is the last word in tech. Join the top tech pundits in a roundtable discussion of the latest trends in high tech. Hosted by Leo Laporte and friends.</p>1648029023https://api.tvmaze.com/shows/17584https://api.tvmaze.com/episodes/2300104NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1001977577https://www.tvmaze.com/episodes/1977577/atop-the-fourth-wall-12x46-the-transformers-uk-41The Transformers (UK) #411246regular2020-12-142020-12-14T17:00:00+00:0025.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197757718971https://www.tvmaze.com/shows/18971/atop-the-fourth-wallAtop the Fourth WallVarietyEnglish[]Running25.025.02008-10-26Nonehttp://www.atopthefourthwall.com[Monday]NaN28NaN40.0BlipUnited StatesUSAmerica/New_YorkNoneNoneNaN247956.0tt1868207https://static.tvmaze.com/uploads/images/medium_portrait/65/164161.jpghttps://static.tvmaze.com/uploads/images/original_untouched/65/164161.jpg<p><b>Atop the Fourth Wall</b> is a comic book review show, hosted by Lewis "Linkara" Lovhaug. The show specializes in reviewing really bad comic books.</p>1660915710https://api.tvmaze.com/shows/18971https://api.tvmaze.com/episodes/2330183https://api.tvmaze.com/episodes/2330184NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1012036538https://www.tvmaze.com/episodes/2036538/raw-talk-4x29-raw-talk-39Raw Talk 39429regular2020-12-142020-12-14T17:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/203653822473https://www.tvmaze.com/shows/22473/raw-talkRAW TalkTalk ShowEnglish[Sports]Running30.030.02016-10-30Nonehttps://watch.wwe.com/in-ring/Raw-Talk-1004[Monday]NaN29NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNoneNaN335558.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/409/1024249.jpghttps://static.tvmaze.com/uploads/images/original_untouched/409/1024249.jpg<p>On <b>RAW Talk</b>, Renee Young catches up with your favorite WWE RAW Superstars after each episode of "RAW" airs on the USA Network to hear their thoughts on all of that evening's action.</p>1660234141https://api.tvmaze.com/shows/22473https://api.tvmaze.com/episodes/2350914https://api.tvmaze.com/episodes/2350915NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1021979360https://www.tvmaze.com/episodes/1979360/death-battle-7x19-sanji-vs-rock-leeSanji vs. Rock Lee719regular2020-12-142020-12-14T17:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197936044725https://www.tvmaze.com/shows/44725/death-battleDeath Battle!AnimationEnglish[Comedy, Action]Running10.010.02010-12-07Nonehttps://roosterteeth.com/series/death-battle[Monday, Sunday]NaN26NaN32.0Rooster TeethUnited StatesUSAmerica/New_YorkNoneNoneNaN254119.0tt4031218https://static.tvmaze.com/uploads/images/medium_portrait/353/884726.jpghttps://static.tvmaze.com/uploads/images/original_untouched/353/884726.jpg<p><b>Death Battle!</b> places two or more characters from pop culture in an all out, no-holds barred slugfest to the death. Who will survive? What weapons will be used? How much blood will be spilled? <i>Death Battle!</i> has the answers.</p>1657808703https://api.tvmaze.com/shows/44725https://api.tvmaze.com/episodes/2361297NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1031977412https://www.tvmaze.com/episodes/1977412/goede-tijden-slechte-tijden-31x61-aflevering-6316Aflevering 63163161regular2020-12-1420:002020-12-14T19:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19774122504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/20:00[Monday, Tuesday, Wednesday, Thursday]NaN84NaNNaNNaNNaNNaNNaNNaNNone19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpgNone1662346277https://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2379701https://api.tvmaze.com/episodes/2379702https://static.tvmaze.com/uploads/images/medium_landscape/288/720704.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/720704.jpg112.0RTL4NetherlandsNLEurope/AmsterdamNaNNaNNaNNaN
1041987074https://www.tvmaze.com/episodes/1987074/frusna-vagar-6x08-episode-8Episode 868regular2020-12-1420:002020-12-14T19:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198707435597https://www.tvmaze.com/shows/35597/frusna-vagarFrusna vägarRealitySwedish[]Running60.060.02018-01-30Nonehttps://www.viafree.se/program/reality/frusna-vagar20:00[Tuesday]NaN12NaN191.0ViafreeNaNNaNNaNNoneNoneNaN341150.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/150/376405.jpghttps://static.tvmaze.com/uploads/images/original_untouched/150/376405.jpg<p>Join a sparkling Sweden far up in the north where snow and ice are everyday for both bearers and snowmen, but not as comfortable for big city residents on a temporary visit. In Frozen roads, we go out on the roads along with the heroes who turn the northern borders into dangerous areas, despite Kung Boro's hard resistance. When the wind suddenly sweeps into the sparkling fields in snowy wrecking, the roads shine glashala and the drifting snow forms piles, then they have never longed so much for the heroes of the winter roads.</p>1644329789https://api.tvmaze.com/shows/35597https://api.tvmaze.com/episodes/2272638NaNNaNNaN558.0TV3SwedenSEEurope/StockholmNaNNaNNaNNaN
1051978063https://www.tvmaze.com/episodes/1978063/prince-charming-2x10-folge-10Folge 10210regular2020-12-1420:152020-12-14T19:15:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197806345015https://www.tvmaze.com/shows/45015/prince-charmingPrince CharmingRealityGerman[Romance]Running60.060.02019-10-30Nonehttps://www.tvnow.de/shows/prince-charming-1774220:15[Tuesday]NaN22NaN368.0RTL+GermanyDEEurope/BusingenNoneNoneNaN371505.0tt11219164https://static.tvmaze.com/uploads/images/medium_portrait/223/558964.jpghttps://static.tvmaze.com/uploads/images/original_untouched/223/558964.jpg<p>German version of a handsome man trying to find true love amongst a group of "princes". Who shall provide the happy ending?</p>1652913157https://api.tvmaze.com/shows/45015https://api.tvmaze.com/episodes/2182395NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1062156738https://www.tvmaze.com/episodes/2156738/curious-george-12x19-georges-new-homeGeorge's New Home1219regular2020-12-1417:002020-12-14T22:00:00+00:0015.0NaNNoneNaNhttps://api.tvmaze.com/episodes/215673817447https://www.tvmaze.com/shows/17447/curious-georgeCurious GeorgeAnimationEnglish[Children, Family]Running15.015.02006-09-04NoneNone17:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN79NaN347.0PeacockUnited StatesUSAmerica/New_Yorkhttps://www.peacocktv.com/NoneNaN79429.0tt0449545https://static.tvmaze.com/uploads/images/medium_portrait/58/147224.jpghttps://static.tvmaze.com/uploads/images/original_untouched/58/147224.jpg<p>George lives to find new things to discover, touch, spill, and chew. Everything is new to George and worth investigating. Of course, in George's hands - all four of them - investigation often leads to unintended consequences! Throughout George's adventures, he encounters and models basic concepts in each of the three content areas.</p>1647702482https://api.tvmaze.com/shows/17447https://api.tvmaze.com/episodes/2298196NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1071972712https://www.tvmaze.com/episodes/1972712/wwe-monday-night-raw-27x50-1438-tropicana-field-in-st-petersburg-fl#1438 - Tropicana Field in St. Petersburg, FL2750regular2020-12-1420:002020-12-15T01:00:00+00:00180.0NaNNoneNaNhttps://api.tvmaze.com/episodes/1972712802https://www.tvmaze.com/shows/802/wwe-monday-night-rawWWE Monday Night RAWSportsEnglish[]Running180.0181.01993-01-11Nonehttp://www.wwe.com/20:00[Monday]7.595NaN15.0WWE NetworkUnited StatesUSAmerica/New_YorkNoneNone6659.076779.0tt0185103https://static.tvmaze.com/uploads/images/medium_portrait/357/892591.jpghttps://static.tvmaze.com/uploads/images/original_untouched/357/892591.jpg<p><b>WWE Monday Night RAW</b> is World Wrestling Entertainment's (formerly the WWF and the WWWF before that) premiere wrestling event and brand. Since its launch in 1993, WWE Monday Night RAW continues to air live on Monday nights. It is generally seen as the company's flagship program due to its prolific history, high ratings, weekly live format, and emphasis on pay-per-views. Monday Night RAW is high profile enough to attract frequent visits from celebrities who usually serve as guest hosts for a single live event. Since its first episode, the show has been broadcast live or recorded from more than 197 different arenas in 165 cities and towns in seven different nations: including the United States, Canada, the United Kingdom twice a year, Afghanistan for a special Tribute to the Troops, Germany, Japan, Italy and Mexico.</p>1659846022https://api.tvmaze.com/shows/802https://api.tvmaze.com/episodes/2348841https://api.tvmaze.com/episodes/2348842NaNNaN30.0USA NetworkUnited StatesUSAmerica/New_YorkNaNNaNNaNNaN
1082152585https://www.tvmaze.com/episodes/2152585/gang-wars-princes-1x10-serija-10Serija 10110regular2020-12-1421:002020-12-15T02:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/215258557009https://www.tvmaze.com/shows/57009/gang-wars-princesGang Wars. PrincesScriptedLithuanian[Drama, Crime, Thriller]EndedNaN45.02020-10-122020-12-28https://go3.lt/series/gauju-karai-princai,serial-2042036[Monday]NaN11NaN518.0Go3NaNNaNNaNNoneNoneNaN401790.0tt13229878https://static.tvmaze.com/uploads/images/medium_portrait/350/876606.jpghttps://static.tvmaze.com/uploads/images/original_untouched/350/876606.jpg<p>Based on true events, the new Go3 original series is a crime story that may have taken place in the late 20th century in Lithuania. The story about one of the criminal groups "Princes" shows their methods of action, lifestyle and relationships with other criminal gangs.</p>1636217065https://api.tvmaze.com/shows/57009https://api.tvmaze.com/episodes/2152587NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN